kittycad.models.ok_modeling_cmd_response

Classes

OptionAddHoleFromOffset(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCameraDragEnd(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCameraDragMove(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCameraDragStart(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCenterOfMass(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionClosePath(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCurveGetControlPoints(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCurveGetEndPoints(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCurveGetType(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionCurveSetConstraint(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraCenterToScene(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraCenterToSelection(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraFocusOn(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraGetSettings(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraGetView(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraLookAt(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraPerspectiveSettings(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraSetOrthographic(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraSetPerspective(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraSetView(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDefaultCameraZoom(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDensity(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionDisableDryRun(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEdgeLinesVisible(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEmpty(**data)	An empty response, used for any command that does not explicitly have a response defined here.
OptionEnableDryRun(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEnableSketchMode(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEngineUtilEvaluatePath(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityCircularPattern(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityClone(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityFade(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetAllChildUuids(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetChildUuid(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetDistance(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetNumChildren(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetParentId(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityGetSketchPaths(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityLinearPattern(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityLinearPatternTransform(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityMakeHelix(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityMakeHelixFromEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityMakeHelixFromParams(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityMirror(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntityMirrorAcrossEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionEntitySetOpacity(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExport(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExport2D(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExport3D(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExtendPath(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExtrude(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionExtrusionFaceInfo(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionFaceGetCenter(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionFaceGetGradient(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionFaceGetPosition(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionFaceIsPlanar(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionGetEntityType(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionGetNumObjects(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionGetSketchModePlane(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionHandleMouseDragEnd(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionHandleMouseDragMove(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionHandleMouseDragStart(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionHighlightSetEntities(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionHighlightSetEntity(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionImportFiles(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionImportedGeometry(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionLoft(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMakeAxesGizmo(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMakeOffsetPath(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMakePlane(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMass(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMouseClick(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMouseMove(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionMovePathPen(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionNewAnnotation(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionObjectBringToFront(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionObjectSetMaterialParamsPbr(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionObjectVisible(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionOrientToFace(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathGetCurveUuid(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathGetCurveUuidsForVertices(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathGetInfo(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathGetSketchTargetUuid(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathGetVertexUuids(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPathSegmentInfo(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPlaneIntersectAndProject(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionPlaneSetColor(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionProjectEntityToPlane(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionProjectPointsToPlane(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionReconfigureStream(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionRemoveSceneObjects(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionRevolve(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionRevolveAboutEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSceneClearAll(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectAdd(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectClear(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectGet(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectRemove(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectReplace(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSelectWithPoint(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSendObject(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetBackgroundColor(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetCurrentToolProperties(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetDefaultSystemProperties(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetGridReferencePlane(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetObjectTransform(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetSceneUnits(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetSelectionFilter(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetSelectionType(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSetTool(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSketchModeDisable(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid2DAddHole(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DFilletEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetAllEdgeFaces(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetAllOppositeEdges(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetCommonEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetExtrusionFaceInfo(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetNextAdjacentEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetOppositeEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DGetPrevAdjacentEdge(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSolid3DShellFace(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionStartPath(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSurfaceArea(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionSweep(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionTakeSnapshot(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionUpdateAnnotation(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionViewIsometric(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionVolume(**data)	Create a new model by parsing and validating input data from keyword arguments.
OptionZoomToFit(**data)	Create a new model by parsing and validating input data from keyword arguments.

class kittycad.models.ok_modeling_cmd_response.OptionAddHoleFromOffset(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.add_hole_from_offset.AddHoleFromOffset'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['add_hole_from_offset']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 929

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionAddHoleFromOffset'>, 'config': {'title': 'OptionAddHoleFromOffset'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionAddHoleFromOffset'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionAddHoleFromOffset:94394503589632', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.add_hole_from_offset.AddHoleFromOffset'>, 'config': {'title': 'AddHoleFromOffset'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.add_hole_from_offset.AddHoleFromOffset'>>]}, 'ref': 'kittycad.models.add_hole_from_offset.AddHoleFromOffset:94394489239600', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'AddHoleFromOffset', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'add_hole_from_offset', 'schema': {'expected': ['add_hole_from_offset'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionAddHoleFromOffset', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=AddHoleFromOffset, required=True), 'type': FieldInfo(annotation=Literal['add_hole_from_offset'], required=False, default='add_hole_from_offset')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedaef00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebeddaab0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "add_hole_from_offset",                                             },                                             expected_py: None,                                             name: "literal['add_hole_from_offset']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9edfff830,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "AddHoleFromOffset",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionAddHoleFromOffset",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionAddHoleFromOffset", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0540,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0630,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebddbfc30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebddbfbf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "AddHoleFromOffset",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9edfff830,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "AddHoleFromOffset",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0690,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0210,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebeddaab0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "add_hole_from_offset": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbfc80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebeddaab0,                                                 ),                                             ],                                         },                                         expected_repr: "'add_hole_from_offset'",                                         name: "literal['add_hole_from_offset']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['add_hole_from_offset']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionAddHoleFromOffset",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedaef00,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionAddHoleFromOffset",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.add_hole_from_offset.AddHoleFromOffset, type: Literal['add_hole_from_offset'] = 'add_hole_from_offset') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: AddHoleFromOffset

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=AddHoleFromOffset, required=True), 'type': FieldInfo(annotation=Literal['add_hole_from_offset'], required=False, default='add_hole_from_offset')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['add_hole_from_offset']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCameraDragEnd(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.camera_drag_end.CameraDragEnd'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['camera_drag_end']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 819

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragEnd'>, 'config': {'title': 'OptionCameraDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragEnd'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragEnd:94394503301440', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_drag_end.CameraDragEnd'>, 'config': {'title': 'CameraDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_drag_end.CameraDragEnd'>>]}, 'ref': 'kittycad.models.camera_drag_end.CameraDragEnd:94394493192672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'CameraDragEnd', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'camera_drag_end', 'schema': {'expected': ['camera_drag_end'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragEnd', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragEnd, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_end'], required=False, default='camera_drag_end')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed68940,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebefa43b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_end",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_end']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee3c49e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CameraDragEnd",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragEnd",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragEnd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7f00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7f30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebdd96b30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebdd96b70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebded6af0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebded69d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebded6c40,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebded6b80,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebdd96a70,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebdd96a30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebded6ca0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebded6c70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebdd96af0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebdd96ab0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebded6cd0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebded6d00,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebded7ea0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebded7ed0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CameraDragEnd",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee3c49e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CameraDragEnd",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7f60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7f90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebefa43b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_end": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd96bc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebefa43b0,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_end'",                                         name: "literal['camera_drag_end']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_end']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragEnd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed68940,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCameraDragEnd",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.camera_drag_end.CameraDragEnd, type: Literal['camera_drag_end'] = 'camera_drag_end') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CameraDragEnd

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragEnd, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_end'], required=False, default='camera_drag_end')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['camera_drag_end']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCameraDragMove(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.camera_drag_move.CameraDragMove'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['camera_drag_move']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 809

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragMove'>, 'config': {'title': 'OptionCameraDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragMove'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragMove:94394503264528', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_drag_move.CameraDragMove'>, 'config': {'title': 'CameraDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_drag_move.CameraDragMove'>>]}, 'ref': 'kittycad.models.camera_drag_move.CameraDragMove:94394493322736', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'CameraDragMove', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'camera_drag_move', 'schema': {'expected': ['camera_drag_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragMove', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragMove, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_move'], required=False, default='camera_drag_move')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed5f910,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebefa6970,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_move",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee3e45f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CameraDragMove",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragMove",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6640,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded64f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebdd94170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebdd941b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebded61c0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebded61f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebded6220,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebded6250,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebdd940b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebdd94070,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebded6280,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebded62b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebdd94130,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebdd940f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebded64c0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebded6400,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebded6430,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebded62e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CameraDragMove",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee3e45f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CameraDragMove",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded63d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6520,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebefa6970,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd94200,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebefa6970,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_move'",                                         name: "literal['camera_drag_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_move']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed5f910,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCameraDragMove",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.camera_drag_move.CameraDragMove, type: Literal['camera_drag_move'] = 'camera_drag_move') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CameraDragMove

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragMove, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_move'], required=False, default='camera_drag_move')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['camera_drag_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCameraDragStart(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.camera_drag_start.CameraDragStart'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['camera_drag_start']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 235

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragStart'>, 'config': {'title': 'OptionCameraDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragStart'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCameraDragStart:94394502595328', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_drag_start.CameraDragStart'>, 'config': {'title': 'CameraDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_drag_start.CameraDragStart'>>]}, 'ref': 'kittycad.models.camera_drag_start.CameraDragStart:94394493342688', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'CameraDragStart', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'camera_drag_start', 'schema': {'expected': ['camera_drag_start'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragStart', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragStart, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_start'], required=False, default='camera_drag_start')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecbc300,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebefa5e30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_start",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_start']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee3e93e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CameraDragStart",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragStart",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragStart", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a2e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9a250,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "CameraDragStart",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee3e93e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CameraDragStart",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde99f50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde99e30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebefa5e30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_start": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd13580,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebefa5e30,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_start'",                                         name: "literal['camera_drag_start']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_start']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragStart",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecbc300,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCameraDragStart",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.camera_drag_start.CameraDragStart, type: Literal['camera_drag_start'] = 'camera_drag_start') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CameraDragStart

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CameraDragStart, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_start'], required=False, default='camera_drag_start')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['camera_drag_start']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCenterOfMass(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.center_of_mass.CenterOfMass'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['center_of_mass']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1271

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCenterOfMass'>, 'config': {'title': 'OptionCenterOfMass'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCenterOfMass'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCenterOfMass:94394504045616', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.center_of_mass.CenterOfMass'>, 'config': {'title': 'CenterOfMass'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.center_of_mass.CenterOfMass'>>]}, 'ref': 'kittycad.models.center_of_mass.CenterOfMass:94394493406848', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center_of_mass': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'output_unit': {'metadata': {}, 'schema': {'cls': <enum 'UnitLength'>, 'members': [UnitLength.CM, UnitLength.FT, UnitLength.IN, UnitLength.M, UnitLength.MM, UnitLength.YD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_length.UnitLength:94394491082416', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'CenterOfMass', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'center_of_mass', 'schema': {'expected': ['center_of_mass'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCenterOfMass', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CenterOfMass, required=True), 'type': FieldInfo(annotation=Literal['center_of_mass'], required=False, default='center_of_mass')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee1e430,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebefa4430,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "center_of_mass",                                             },                                             expected_py: None,                                             name: "literal['center_of_mass']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee3f8e80,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "output_unit": SerField {                                                     key_py: Py(                                                         0x00007f1ebebb86b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee1c16b0,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "center_of_mass": SerField {                                                     key_py: Py(                                                         0x00007f1ebefa4430,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9edd655a0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "x": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08838,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08868,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "z": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08898,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 3,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "Point3d",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CenterOfMass",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCenterOfMass",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCenterOfMass", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1890,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1260,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "center_of_mass",                                                 lookup_key: Simple {                                                     key: "center_of_mass",                                                     py_key: Py(                                                         0x00007f1ebddeaff0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "center_of_mass",                                                                 Py(                                                                     0x00007f1ebddeafb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebefa4430,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "x",                                                                         lookup_key: Simple {                                                                             key: "x",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08838,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "x",                                                                                         Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08838,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "y",                                                                         lookup_key: Simple {                                                                             key: "y",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08868,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "y",                                                                                         Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08868,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "z",                                                                         lookup_key: Simple {                                                                             key: "z",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08898,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "z",                                                                                         Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08898,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "Point3d",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9edd655a0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "Point3d",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "output_unit",                                                 lookup_key: Simple {                                                     key: "output_unit",                                                     py_key: Py(                                                         0x00007f1ebddeb0b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "output_unit",                                                                 Py(                                                                     0x00007f1ebddeb0f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebebb86b0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee1c16b0,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "in": 2,                                                                     "mm": 4,                                                                     "yd": 5,                                                                     "m": 3,                                                                     "ft": 1,                                                                     "cm": 0,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebddeb040,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebebce630,                                                                 ),                                                                 Py(                                                                     0x00007f1ebebce810,                                                                 ),                                                                 Py(                                                                     0x00007f1ebebcdc70,                                                                 ),                                                                 Py(                                                                     0x00007f1ebebcd370,                                                                 ),                                                                 Py(                                                                     0x00007f1ebebccad0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebebcebd0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'cm', 'ft', 'in', 'm', 'mm' or 'yd'",                                                         strict: false,                                                         class_repr: "UnitLength",                                                         name: "str-enum[UnitLength]",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CenterOfMass",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee3f8e80,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CenterOfMass",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1080,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0f60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebefa4430,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "center_of_mass": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddeb140,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebefa4430,                                                 ),                                             ],                                         },                                         expected_repr: "'center_of_mass'",                                         name: "literal['center_of_mass']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['center_of_mass']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCenterOfMass",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee1e430,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCenterOfMass",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.center_of_mass.CenterOfMass, type: Literal['center_of_mass'] = 'center_of_mass') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CenterOfMass

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CenterOfMass, required=True), 'type': FieldInfo(annotation=Literal['center_of_mass'], required=False, default='center_of_mass')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['center_of_mass']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionClosePath(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.close_path.ClosePath'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['close_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 799

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionClosePath'>, 'config': {'title': 'OptionClosePath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionClosePath'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionClosePath:94394503253280', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.close_path.ClosePath'>, 'config': {'title': 'ClosePath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.close_path.ClosePath'>>]}, 'ref': 'kittycad.models.close_path.ClosePath:94394493431056', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'face_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ClosePath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'close_path', 'schema': {'expected': ['close_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionClosePath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ClosePath, required=True), 'type': FieldInfo(annotation=Literal['close_path'], required=False, default='close_path')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed5cd20,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee3fed10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "face_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebeddda10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ClosePath",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf564030,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "close_path",                                             },                                             expected_py: None,                                             name: "literal['close_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionClosePath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionClosePath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5b30,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5ad0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "face_id",                                                 lookup_key: Simple {                                                     key: "face_id",                                                     py_key: Py(                                                         0x00007f1ebded5980,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "face_id",                                                                 Py(                                                                     0x00007f1ebded5b00,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeddda10,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ClosePath",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee3fed10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ClosePath",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5bc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5b90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf564030,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "close_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd8d840,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf564030,                                                 ),                                             ],                                         },                                         expected_repr: "'close_path'",                                         name: "literal['close_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['close_path']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionClosePath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed5cd20,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionClosePath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.close_path.ClosePath, type: Literal['close_path'] = 'close_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ClosePath

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ClosePath, required=True), 'type': FieldInfo(annotation=Literal['close_path'], required=False, default='close_path')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['close_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCurveGetControlPoints(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.curve_get_control_points.CurveGetControlPoints'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_control_points']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1029

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetControlPoints'>, 'config': {'title': 'OptionCurveGetControlPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetControlPoints'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetControlPoints:94394500581888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.curve_get_control_points.CurveGetControlPoints'>, 'config': {'title': 'CurveGetControlPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.curve_get_control_points.CurveGetControlPoints'>>]}, 'ref': 'kittycad.models.curve_get_control_points.CurveGetControlPoints:94394493906144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'control_points': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'CurveGetControlPoints', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'curve_get_control_points', 'schema': {'expected': ['curve_get_control_points'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetControlPoints', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetControlPoints, required=True), 'type': FieldInfo(annotation=Literal['curve_get_control_points'], required=False, default='curve_get_control_points')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eead0a00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee472ce0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "control_points": SerField {                                                     key_py: Py(                                                         0x00007f1ebe3bdcf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9edd655a0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "z": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "x": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "y": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 3,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "Point3d",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[Point3d]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CurveGetControlPoints",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee496b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_control_points",                                             },                                             expected_py: None,                                             name: "literal['curve_get_control_points']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetControlPoints",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetControlPoints", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34ab0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35500,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "control_points",                                                 lookup_key: Simple {                                                     key: "control_points",                                                     py_key: Py(                                                         0x00007f1ebddba530,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "control_points",                                                                 Py(                                                                     0x00007f1ebddbbdb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe3bdcf0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "x",                                                                                     lookup_key: Simple {                                                                                         key: "x",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "x",                                                                                                     Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08838,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "y",                                                                                     lookup_key: Simple {                                                                                         key: "y",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "y",                                                                                                     Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08868,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "z",                                                                                     lookup_key: Simple {                                                                                         key: "z",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "z",                                                                                                     Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08898,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "Point3d",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9edd655a0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "Point3d",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CurveGetControlPoints",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee472ce0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CurveGetControlPoints",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35260,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd350e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee496b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_control_points": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddb9f80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee496b0,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_control_points'",                                         name: "literal['curve_get_control_points']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_control_points']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetControlPoints",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eead0a00,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCurveGetControlPoints",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.curve_get_control_points.CurveGetControlPoints, type: Literal['curve_get_control_points'] = 'curve_get_control_points') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CurveGetControlPoints

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetControlPoints, required=True), 'type': FieldInfo(annotation=Literal['curve_get_control_points'], required=False, default='curve_get_control_points')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_control_points']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCurveGetEndPoints(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.curve_get_end_points.CurveGetEndPoints'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_end_points']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1151

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetEndPoints'>, 'config': {'title': 'OptionCurveGetEndPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetEndPoints'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetEndPoints:94394503850880', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.curve_get_end_points.CurveGetEndPoints'>, 'config': {'title': 'CurveGetEndPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.curve_get_end_points.CurveGetEndPoints'>>]}, 'ref': 'kittycad.models.curve_get_end_points.CurveGetEndPoints:94394493914224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'start': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CurveGetEndPoints', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'curve_get_end_points', 'schema': {'expected': ['curve_get_end_points'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetEndPoints', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetEndPoints, required=True), 'type': FieldInfo(annotation=Literal['curve_get_end_points'], required=False, default='curve_get_end_points')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedeeb80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee474c70,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "end": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f02590,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "start": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f06338,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CurveGetEndPoints",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf567230,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_end_points",                                             },                                             expected_py: None,                                             name: "literal['curve_get_end_points']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetEndPoints",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetEndPoints", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2910,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2940,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "end",                                                 lookup_key: Simple {                                                     key: "end",                                                     py_key: Py(                                                         0x00007f1ebdda2850,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "end",                                                                 Py(                                                                     0x00007f1ebdda2880,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f02590,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "start",                                                 lookup_key: Simple {                                                     key: "start",                                                     py_key: Py(                                                         0x00007f1ebdda28b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "start",                                                                 Py(                                                                     0x00007f1ebdda28e0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f06338,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CurveGetEndPoints",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee474c70,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CurveGetEndPoints",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2970,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda29a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf567230,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_end_points": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde1a40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf567230,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_end_points'",                                         name: "literal['curve_get_end_points']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_end_points']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetEndPoints",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedeeb80,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCurveGetEndPoints",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.curve_get_end_points.CurveGetEndPoints, type: Literal['curve_get_end_points'] = 'curve_get_end_points') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CurveGetEndPoints

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetEndPoints, required=True), 'type': FieldInfo(annotation=Literal['curve_get_end_points'], required=False, default='curve_get_end_points')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_end_points']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCurveGetType(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.curve_get_type.CurveGetType'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1059

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetType'>, 'config': {'title': 'OptionCurveGetType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetType'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCurveGetType:94394503724608', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.curve_get_type.CurveGetType'>, 'config': {'title': 'CurveGetType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.curve_get_type.CurveGetType'>>]}, 'ref': 'kittycad.models.curve_get_type.CurveGetType:94394493858768', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_type': {'metadata': {}, 'schema': {'cls': <enum 'CurveType'>, 'members': [CurveType.LINE, CurveType.ARC, CurveType.NURBS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.curve_type.CurveType:94394493926032', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'CurveGetType', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'curve_get_type', 'schema': {'expected': ['curve_get_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetType, required=True), 'type': FieldInfo(annotation=Literal['curve_get_type'], required=False, default='curve_get_type')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedcfe40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf564430,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_type",                                             },                                             expected_py: None,                                             name: "literal['curve_get_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4673d0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "curve_type": SerField {                                                     key_py: Py(                                                         0x00007f1ebf5649f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee477a90,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CurveGetType",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99830,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde99650,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "curve_type",                                                 lookup_key: Simple {                                                     key: "curve_type",                                                     py_key: Py(                                                         0x00007f1ebdd1d870,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "curve_type",                                                                 Py(                                                                     0x00007f1ebdd1f230,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf5649f0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee477a90,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "arc": 1,                                                                     "line": 0,                                                                     "nurbs": 2,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdd1eb00,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe302e70,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe302ed0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe302f30,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'line', 'arc' or 'nurbs'",                                                         strict: false,                                                         class_repr: "CurveType",                                                         name: "str-enum[CurveType]",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "CurveGetType",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4673d0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CurveGetType",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b660,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9ad60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf564430,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1f300,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf564430,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_type'",                                         name: "literal['curve_get_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_type']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedcfe40,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCurveGetType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.curve_get_type.CurveGetType, type: Literal['curve_get_type'] = 'curve_get_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CurveGetType

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveGetType, required=True), 'type': FieldInfo(annotation=Literal['curve_get_type'], required=False, default='curve_get_type')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionCurveSetConstraint(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.curve_set_constraint.CurveSetConstraint'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['curve_set_constraint']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 497

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveSetConstraint'>, 'config': {'title': 'OptionCurveSetConstraint'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionCurveSetConstraint'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionCurveSetConstraint:94394502920336', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.curve_set_constraint.CurveSetConstraint'>, 'config': {'title': 'CurveSetConstraint'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.curve_set_constraint.CurveSetConstraint'>>]}, 'ref': 'kittycad.models.curve_set_constraint.CurveSetConstraint:94394493904400', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'CurveSetConstraint', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'curve_set_constraint', 'schema': {'expected': ['curve_set_constraint'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveSetConstraint', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveSetConstraint, required=True), 'type': FieldInfo(annotation=Literal['curve_set_constraint'], required=False, default='curve_set_constraint')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed0b890,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee472610,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "CurveSetConstraint",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf5645b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_set_constraint",                                             },                                             expected_py: None,                                             name: "literal['curve_set_constraint']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveSetConstraint",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveSetConstraint", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd365b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36400,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "CurveSetConstraint",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee472610,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "CurveSetConstraint",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd364c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd37030,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf5645b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_set_constraint": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd4b880,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf5645b0,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_set_constraint'",                                         name: "literal['curve_set_constraint']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_set_constraint']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveSetConstraint",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed0b890,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionCurveSetConstraint",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.curve_set_constraint.CurveSetConstraint, type: Literal['curve_set_constraint'] = 'curve_set_constraint') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: CurveSetConstraint

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=CurveSetConstraint, required=True), 'type': FieldInfo(annotation=Literal['curve_set_constraint'], required=False, default='curve_set_constraint')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_set_constraint']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToScene(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_center_to_scene.DefaultCameraCenterToScene'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_center_to_scene']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 669

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToScene'>, 'config': {'title': 'OptionDefaultCameraCenterToScene'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToScene'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToScene:94394503081168', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_center_to_scene.DefaultCameraCenterToScene'>, 'config': {'title': 'DefaultCameraCenterToScene'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_center_to_scene.DefaultCameraCenterToScene'>>]}, 'ref': 'kittycad.models.default_camera_center_to_scene.DefaultCameraCenterToScene:94394494377136', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraCenterToScene', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_center_to_scene', 'schema': {'expected': ['default_camera_center_to_scene'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraCenterToScene', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraCenterToScene, required=True), 'type': FieldInfo(annotation=Literal['default_camera_center_to_scene'], required=False, default='default_camera_center_to_scene')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed32cd0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4e5cb0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraCenterToScene",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49700,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_center_to_scene",                                             },                                             expected_py: None,                                             name: "literal['default_camera_center_to_scene']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraCenterToScene",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraCenterToScene", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded78a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded78d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraCenterToScene",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4e5cb0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraCenterToScene",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7900,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49700,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_center_to_scene": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd74500,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49700,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_center_to_scene'",                                         name: "literal['default_camera_center_to_scene']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_center_to_scene']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraCenterToScene",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed32cd0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraCenterToScene",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_center_to_scene.DefaultCameraCenterToScene, type: Literal['default_camera_center_to_scene'] = 'default_camera_center_to_scene') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraCenterToScene

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraCenterToScene, required=True), 'type': FieldInfo(annotation=Literal['default_camera_center_to_scene'], required=False, default='default_camera_center_to_scene')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_center_to_scene']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToSelection(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_center_to_selection.DefaultCameraCenterToSelection'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_center_to_selection']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 657

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToSelection'>, 'config': {'title': 'OptionDefaultCameraCenterToSelection'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToSelection'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraCenterToSelection:94394503071424', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_center_to_selection.DefaultCameraCenterToSelection'>, 'config': {'title': 'DefaultCameraCenterToSelection'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_center_to_selection.DefaultCameraCenterToSelection'>>]}, 'ref': 'kittycad.models.default_camera_center_to_selection.DefaultCameraCenterToSelection:94394494383536', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraCenterToSelection', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_center_to_selection', 'schema': {'expected': ['default_camera_center_to_selection'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraCenterToSelection', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraCenterToSelection, required=True), 'type': FieldInfo(annotation=Literal['default_camera_center_to_selection'], required=False, default='default_camera_center_to_selection')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed306c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4e75b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraCenterToSelection",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49840,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_center_to_selection",                                             },                                             expected_py: None,                                             name: "literal['default_camera_center_to_selection']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraCenterToSelection",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraCenterToSelection", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7510,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7540,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraCenterToSelection",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4e75b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraCenterToSelection",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7570,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded75a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49840,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_center_to_selection": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd6b600,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49840,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_center_to_selection'",                                         name: "literal['default_camera_center_to_selection']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_center_to_selection']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraCenterToSelection",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed306c0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraCenterToSelection",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_center_to_selection.DefaultCameraCenterToSelection, type: Literal['default_camera_center_to_selection'] = 'default_camera_center_to_selection') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraCenterToSelection

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraCenterToSelection, required=True), 'type': FieldInfo(annotation=Literal['default_camera_center_to_selection'], required=False, default='default_camera_center_to_selection')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_center_to_selection']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraFocusOn(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_focus_on.DefaultCameraFocusOn'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_focus_on']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 939

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraFocusOn'>, 'config': {'title': 'OptionDefaultCameraFocusOn'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraFocusOn'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraFocusOn:94394503601872', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_focus_on.DefaultCameraFocusOn'>, 'config': {'title': 'DefaultCameraFocusOn'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_focus_on.DefaultCameraFocusOn'>>]}, 'ref': 'kittycad.models.default_camera_focus_on.DefaultCameraFocusOn:94394494373264', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraFocusOn', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_focus_on', 'schema': {'expected': ['default_camera_focus_on'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraFocusOn', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraFocusOn, required=True), 'type': FieldInfo(annotation=Literal['default_camera_focus_on'], required=False, default='default_camera_focus_on')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedb1ed0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5e730,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_focus_on",                                             },                                             expected_py: None,                                             name: "literal['default_camera_focus_on']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4e4d90,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraFocusOn",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraFocusOn",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraFocusOn", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0a50,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0a80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraFocusOn",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4e4d90,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraFocusOn",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0ab0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0ae0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5e730,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_focus_on": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddc8b80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5e730,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_focus_on'",                                         name: "literal['default_camera_focus_on']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_focus_on']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraFocusOn",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedb1ed0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraFocusOn",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_focus_on.DefaultCameraFocusOn, type: Literal['default_camera_focus_on'] = 'default_camera_focus_on') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraFocusOn

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraFocusOn, required=True), 'type': FieldInfo(annotation=Literal['default_camera_focus_on'], required=False, default='default_camera_focus_on')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_focus_on']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetSettings(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_get_settings.DefaultCameraGetSettings'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_get_settings']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 829

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetSettings'>, 'config': {'title': 'OptionDefaultCameraGetSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetSettings'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetSettings:94394503337872', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_get_settings.DefaultCameraGetSettings'>, 'config': {'title': 'DefaultCameraGetSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_get_settings.DefaultCameraGetSettings'>>]}, 'ref': 'kittycad.models.default_camera_get_settings.DefaultCameraGetSettings:94394494370672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'DefaultCameraGetSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_get_settings', 'schema': {'expected': ['default_camera_get_settings'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraGetSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraGetSettings, required=True), 'type': FieldInfo(annotation=Literal['default_camera_get_settings'], required=False, default='default_camera_get_settings')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed71790,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49890,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_get_settings",                                             },                                             expected_py: None,                                             name: "literal['default_camera_get_settings']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4e4370,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraGetSettings",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraGetSettings",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraGetSettings", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0480,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda04b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebddad5b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebddad5f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebdda02a0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebdda02d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebdda0300,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebdda0330,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebddad4f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebddad4b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebdda0360,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebdda0390,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebddad570,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebddad530,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebdda03c0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebdda03f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebdda0420,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebdda0450,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "DefaultCameraGetSettings",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4e4370,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraGetSettings",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda04e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0510,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49890,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_get_settings": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddad640,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49890,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_get_settings'",                                         name: "literal['default_camera_get_settings']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_get_settings']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraGetSettings",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed71790,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraGetSettings",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_get_settings.DefaultCameraGetSettings, type: Literal['default_camera_get_settings'] = 'default_camera_get_settings') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraGetSettings

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraGetSettings, required=True), 'type': FieldInfo(annotation=Literal['default_camera_get_settings'], required=False, default='default_camera_get_settings')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_get_settings']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetView(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_get_view.DefaultCameraGetView'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_get_view']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 839

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetView'>, 'config': {'title': 'OptionDefaultCameraGetView'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetView'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraGetView:94394503374528', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_get_view.DefaultCameraGetView'>, 'config': {'title': 'DefaultCameraGetView'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_get_view.DefaultCameraGetView'>>]}, 'ref': 'kittycad.models.default_camera_get_view.DefaultCameraGetView:94394494422992', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'view': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_view_state.CameraViewState'>, 'config': {'title': 'CameraViewState'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_view_state.CameraViewState'>>]}, 'ref': 'kittycad.models.camera_view_state.CameraViewState:94394493293360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'eye_offset': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'is_ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale_enabled': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale_factor': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'pivot_position': {'metadata': {}, 'schema': {'items_schema': {'type': 'float'}, 'type': 'list'}, 'type': 'model-field'}, 'pivot_rotation': {'metadata': {}, 'schema': {'items_schema': {'type': 'float'}, 'type': 'list'}, 'type': 'model-field'}, 'world_coord_system': {'metadata': {}, 'schema': {'cls': <enum 'WorldCoordinateSystem'>, 'members': [WorldCoordinateSystem.RIGHT_HANDED_UP_Z, WorldCoordinateSystem.RIGHT_HANDED_UP_Y], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.world_coordinate_system.WorldCoordinateSystem:94394493341696', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'CameraViewState', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'DefaultCameraGetView', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_get_view', 'schema': {'expected': ['default_camera_get_view'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraGetView', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraGetView, required=True), 'type': FieldInfo(annotation=Literal['default_camera_get_view'], required=False, default='default_camera_get_view')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed7a6c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4f0fd0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "view": SerField {                                                     key_py: Py(                                                         0x00007f1ec1fa6520,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3dd330,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "pivot_rotation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35d1f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     List(                                                                                         ListSerializer {                                                                                             item_serializer: Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                             filter: SchemaFilter {                                                                                                 include: None,                                                                                                 exclude: None,                                                                                             },                                                                                             name: "list[float]",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale_enabled": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35d0b0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "world_coord_system": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35e270,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Enum(                                                                                         EnumSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3e9000,                                                                                             ),                                                                                             serializer: Some(                                                                                                 Str(                                                                                                     StrSerializer,                                                                                                 ),                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pivot_position": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35d1b0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     List(                                                                                         ListSerializer {                                                                                             item_serializer: Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                             filter: SchemaFilter {                                                                                                 include: None,                                                                                                 exclude: None,                                                                                             },                                                                                             name: "list[float]",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale_factor": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35d170,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "eye_offset": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35c3f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "is_ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe35d030,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 8,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraViewState",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraGetView",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5d530,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_get_view",                                             },                                             expected_py: None,                                             name: "literal['default_camera_get_view']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraGetView",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraGetView", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda08d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0900,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "view",                                                 lookup_key: Simple {                                                     key: "view",                                                     py_key: Py(                                                         0x00007f1ebdda0870,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "view",                                                                 Py(                                                                     0x00007f1ebdda08a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1fa6520,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "eye_offset",                                                                         lookup_key: Simple {                                                                             key: "eye_offset",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf3f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "eye_offset",                                                                                         Py(                                                                                             0x00007f1ebddaf3b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35c3f0,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebdda0810,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebdda0840,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "is_ortho",                                                                         lookup_key: Simple {                                                                             key: "is_ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf470,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "is_ortho",                                                                                         Py(                                                                                             0x00007f1ebddaf430,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35d030,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale_enabled",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale_enabled",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf4b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale_enabled",                                                                                         Py(                                                                                             0x00007f1ebddaf4f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35d0b0,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale_factor",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale_factor",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf530,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale_factor",                                                                                         Py(                                                                                             0x00007f1ebddaf570,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35d170,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pivot_position",                                                                         lookup_key: Simple {                                                                             key: "pivot_position",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf5b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pivot_position",                                                                                         Py(                                                                                             0x00007f1ebddaf5f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35d1b0,                                                                         ),                                                                         validator: List(                                                                             ListValidator {                                                                                 strict: false,                                                                                 item_validator: Some(                                                                                     Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 min_length: None,                                                                                 max_length: None,                                                                                 name: OnceLock(                                                                                     <uninit>,                                                                                 ),                                                                                 fail_fast: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pivot_rotation",                                                                         lookup_key: Simple {                                                                             key: "pivot_rotation",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf630,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pivot_rotation",                                                                                         Py(                                                                                             0x00007f1ebddaf670,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35d1f0,                                                                         ),                                                                         validator: List(                                                                             ListValidator {                                                                                 strict: false,                                                                                 item_validator: Some(                                                                                     Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 min_length: None,                                                                                 max_length: None,                                                                                 name: OnceLock(                                                                                     <uninit>,                                                                                 ),                                                                                 fail_fast: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "world_coord_system",                                                                         lookup_key: Simple {                                                                             key: "world_coord_system",                                                                             py_key: Py(                                                                                 0x00007f1ebddaf730,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "world_coord_system",                                                                                         Py(                                                                                             0x00007f1ebddaf770,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe35e270,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055d9ee3e9000,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "right_handed_up_z": 0,                                                                                             "right_handed_up_y": 1,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     expected_py_primitives: Some(                                                                                         Py(                                                                                             0x00007f1ebddaf700,                                                                                         ),                                                                                     ),                                                                                     values: [                                                                                         Py(                                                                                             0x00007f1ebe3004d0,                                                                                         ),                                                                                         Py(                                                                                             0x00007f1ebe300530,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'right_handed_up_z' or 'right_handed_up_y'",                                                                                 strict: false,                                                                                 class_repr: "WorldCoordinateSystem",                                                                                 name: "str-enum[WorldCoordinateSystem]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraViewState",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3dd330,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraViewState",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "DefaultCameraGetView",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4f0fd0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraGetView",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0930,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0960,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5d530,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_get_view": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddaf7c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5d530,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_get_view'",                                         name: "literal['default_camera_get_view']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_get_view']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraGetView",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed7a6c0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraGetView",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_get_view.DefaultCameraGetView, type: Literal['default_camera_get_view'] = 'default_camera_get_view') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraGetView

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraGetView, required=True), 'type': FieldInfo(annotation=Literal['default_camera_get_view'], required=False, default='default_camera_get_view')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_get_view']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraLookAt(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_look_at.DefaultCameraLookAt'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_look_at']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 245

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraLookAt'>, 'config': {'title': 'OptionDefaultCameraLookAt'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraLookAt'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraLookAt:94394502251616', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_look_at.DefaultCameraLookAt'>, 'config': {'title': 'DefaultCameraLookAt'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_look_at.DefaultCameraLookAt'>>]}, 'ref': 'kittycad.models.default_camera_look_at.DefaultCameraLookAt:94394494444064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraLookAt', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_look_at', 'schema': {'expected': ['default_camera_look_at'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraLookAt', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraLookAt, required=True), 'type': FieldInfo(annotation=Literal['default_camera_look_at'], required=False, default='default_camera_look_at')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec68460,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4f6220,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraLookAt",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5fab0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_look_at",                                             },                                             expected_py: None,                                             name: "literal['default_camera_look_at']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraLookAt",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraLookAt", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99bf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde99b00,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraLookAt",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4f6220,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraLookAt",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde99cb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde99a10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5fab0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_look_at": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd127c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5fab0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_look_at'",                                         name: "literal['default_camera_look_at']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_look_at']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraLookAt",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec68460,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraLookAt",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_look_at.DefaultCameraLookAt, type: Literal['default_camera_look_at'] = 'default_camera_look_at') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraLookAt

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraLookAt, required=True), 'type': FieldInfo(annotation=Literal['default_camera_look_at'], required=False, default='default_camera_look_at')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_look_at']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraPerspectiveSettings(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_perspective_settings.DefaultCameraPerspectiveSettings'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_perspective_settings']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 255

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraPerspectiveSettings'>, 'config': {'title': 'OptionDefaultCameraPerspectiveSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraPerspectiveSettings'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraPerspectiveSettings:94394502261120', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_perspective_settings.DefaultCameraPerspectiveSettings'>, 'config': {'title': 'DefaultCameraPerspectiveSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_perspective_settings.DefaultCameraPerspectiveSettings'>>]}, 'ref': 'kittycad.models.default_camera_perspective_settings.DefaultCameraPerspectiveSettings:94394494462448', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraPerspectiveSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_perspective_settings', 'schema': {'expected': ['default_camera_perspective_settings'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraPerspectiveSettings', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraPerspectiveSettings, required=True), 'type': FieldInfo(annotation=Literal['default_camera_perspective_settings'], required=False, default='default_camera_perspective_settings')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec6a980,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4fa9f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraPerspectiveSettings",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49a70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_perspective_settings",                                             },                                             expected_py: None,                                             name: "literal['default_camera_perspective_settings']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraPerspectiveSettings",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraPerspectiveSettings", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5410,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded53b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraPerspectiveSettings",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4fa9f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraPerspectiveSettings",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5380,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5320,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49a70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_perspective_settings": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd11940,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49a70,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_perspective_settings'",                                         name: "literal['default_camera_perspective_settings']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_perspective_settings']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraPerspectiveSettings",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec6a980,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraPerspectiveSettings",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_perspective_settings.DefaultCameraPerspectiveSettings, type: Literal['default_camera_perspective_settings'] = 'default_camera_perspective_settings') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraPerspectiveSettings

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraPerspectiveSettings, required=True), 'type': FieldInfo(annotation=Literal['default_camera_perspective_settings'], required=False, default='default_camera_perspective_settings')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_perspective_settings']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetOrthographic(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_set_orthographic.DefaultCameraSetOrthographic'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_set_orthographic']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 637

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetOrthographic'>, 'config': {'title': 'OptionDefaultCameraSetOrthographic'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetOrthographic'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetOrthographic:94394503052224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_set_orthographic.DefaultCameraSetOrthographic'>, 'config': {'title': 'DefaultCameraSetOrthographic'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_set_orthographic.DefaultCameraSetOrthographic'>>]}, 'ref': 'kittycad.models.default_camera_set_orthographic.DefaultCameraSetOrthographic:94394494461104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraSetOrthographic', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_set_orthographic', 'schema': {'expected': ['default_camera_set_orthographic'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraSetOrthographic', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetOrthographic, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_orthographic'], required=False, default='default_camera_set_orthographic')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed2bbc0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49b60,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_set_orthographic",                                             },                                             expected_py: None,                                             name: "literal['default_camera_set_orthographic']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4fa4b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraSetOrthographic",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraSetOrthographic",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraSetOrthographic", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6e80,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraSetOrthographic",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4fa4b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraSetOrthographic",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6ee0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6f10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49b60,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_set_orthographic": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd697c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49b60,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_set_orthographic'",                                         name: "literal['default_camera_set_orthographic']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_set_orthographic']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraSetOrthographic",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed2bbc0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraSetOrthographic",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_set_orthographic.DefaultCameraSetOrthographic, type: Literal['default_camera_set_orthographic'] = 'default_camera_set_orthographic') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraSetOrthographic

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetOrthographic, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_orthographic'], required=False, default='default_camera_set_orthographic')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_set_orthographic']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetPerspective(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_set_perspective.DefaultCameraSetPerspective'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_set_perspective']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 647

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetPerspective'>, 'config': {'title': 'OptionDefaultCameraSetPerspective'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetPerspective'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetPerspective:94394503061680', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_set_perspective.DefaultCameraSetPerspective'>, 'config': {'title': 'DefaultCameraSetPerspective'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_set_perspective.DefaultCameraSetPerspective'>>]}, 'ref': 'kittycad.models.default_camera_set_perspective.DefaultCameraSetPerspective:94394494471680', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraSetPerspective', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_set_perspective', 'schema': {'expected': ['default_camera_set_perspective'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraSetPerspective', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetPerspective, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_perspective'], required=False, default='default_camera_set_perspective')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed2e0b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4fce00,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraSetPerspective",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49c00,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_set_perspective",                                             },                                             expected_py: None,                                             name: "literal['default_camera_set_perspective']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraSetPerspective",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraSetPerspective", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded71b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded71e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraSetPerspective",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4fce00,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraSetPerspective",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7210,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7240,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49c00,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_set_perspective": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd6a6c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49c00,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_set_perspective'",                                         name: "literal['default_camera_set_perspective']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_set_perspective']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraSetPerspective",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed2e0b0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraSetPerspective",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_set_perspective.DefaultCameraSetPerspective, type: Literal['default_camera_set_perspective'] = 'default_camera_set_perspective') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraSetPerspective

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetPerspective, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_perspective'], required=False, default='default_camera_set_perspective')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_set_perspective']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetView(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_set_view.DefaultCameraSetView'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_set_view']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 849

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetView'>, 'config': {'title': 'OptionDefaultCameraSetView'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetView'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraSetView:94394503400624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_set_view.DefaultCameraSetView'>, 'config': {'title': 'DefaultCameraSetView'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_set_view.DefaultCameraSetView'>>]}, 'ref': 'kittycad.models.default_camera_set_view.DefaultCameraSetView:94394494458960', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DefaultCameraSetView', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_set_view', 'schema': {'expected': ['default_camera_set_view'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraSetView', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetView, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_view'], required=False, default='default_camera_set_view')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed80cb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4f9c50,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraSetView",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5fc30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_set_view",                                             },                                             expected_py: None,                                             name: "literal['default_camera_set_view']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraSetView",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraSetView", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6130,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5ec0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DefaultCameraSetView",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4f9c50,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraSetView",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5e30,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6040,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5fc30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_set_view": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd0a080,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5fc30,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_set_view'",                                         name: "literal['default_camera_set_view']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_set_view']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraSetView",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed80cb0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraSetView",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_set_view.DefaultCameraSetView, type: Literal['default_camera_set_view'] = 'default_camera_set_view') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraSetView

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraSetView, required=True), 'type': FieldInfo(annotation=Literal['default_camera_set_view'], required=False, default='default_camera_set_view')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_set_view']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraZoom(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.default_camera_zoom.DefaultCameraZoom'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_zoom']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 859

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraZoom'>, 'config': {'title': 'OptionDefaultCameraZoom'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraZoom'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDefaultCameraZoom:94394503409856', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.default_camera_zoom.DefaultCameraZoom'>, 'config': {'title': 'DefaultCameraZoom'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.default_camera_zoom.DefaultCameraZoom'>>]}, 'ref': 'kittycad.models.default_camera_zoom.DefaultCameraZoom:94394494470016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'DefaultCameraZoom', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'default_camera_zoom', 'schema': {'expected': ['default_camera_zoom'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraZoom', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraZoom, required=True), 'type': FieldInfo(annotation=Literal['default_camera_zoom'], required=False, default='default_camera_zoom')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed830c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4fc780,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DefaultCameraZoom",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5fb30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_zoom",                                             },                                             expected_py: None,                                             name: "literal['default_camera_zoom']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraZoom",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraZoom", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7060,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded70c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebdd8e5b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebdd8e0b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebded53e0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebded5590,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebded5470,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebded6d30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebdd8e6b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebdd8e630,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebded54d0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebded5800,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebdd8e530,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebdd8e730,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebded5230,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebded6f70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebded7090,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebded6fa0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "DefaultCameraZoom",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4fc780,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DefaultCameraZoom",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6e50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6f40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5fb30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_zoom": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd8dbc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5fb30,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_zoom'",                                         name: "literal['default_camera_zoom']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_zoom']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraZoom",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed830c0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDefaultCameraZoom",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.default_camera_zoom.DefaultCameraZoom, type: Literal['default_camera_zoom'] = 'default_camera_zoom') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DefaultCameraZoom

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DefaultCameraZoom, required=True), 'type': FieldInfo(annotation=Literal['default_camera_zoom'], required=False, default='default_camera_zoom')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_zoom']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDensity(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.density.Density'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['density']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1251

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDensity'>, 'config': {'title': 'OptionDensity'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDensity'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDensity:94394504014064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.density.Density'>, 'config': {'title': 'Density'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.density.Density'>>]}, 'ref': 'kittycad.models.density.Density:94394494497520', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'density': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'output_unit': {'metadata': {}, 'schema': {'cls': <enum 'UnitDensity'>, 'members': [UnitDensity.LB_FT3, UnitDensity.KG_M3], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_density.UnitDensity:94394491864672', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'Density', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'density', 'schema': {'expected': ['density'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDensity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Density, required=True), 'type': FieldInfo(annotation=Literal['density'], required=False, default='density')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee168f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ec00d7660,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "density",                                             },                                             expected_py: None,                                             name: "literal['density']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee5032f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "density": SerField {                                                     key_py: Py(                                                         0x00007f1ec00d7660,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "output_unit": SerField {                                                     key_py: Py(                                                         0x00007f1ebebb86b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee280660,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Density",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDensity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDensity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2370,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda06f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "density",                                                 lookup_key: Simple {                                                     key: "density",                                                     py_key: Py(                                                         0x00007f1ebdda2220,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "density",                                                                 Py(                                                                     0x00007f1ebdda2310,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec00d7660,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "output_unit",                                                 lookup_key: Simple {                                                     key: "output_unit",                                                     py_key: Py(                                                         0x00007f1ebdde8570,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "output_unit",                                                                 Py(                                                                     0x00007f1ebdde8530,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebebb86b0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee280660,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "lb:ft3": 0,                                                                     "kg:m3": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdde84c0,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe5f1970,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f19d0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'lb:ft3' or 'kg:m3'",                                                         strict: false,                                                         class_repr: "UnitDensity",                                                         name: "str-enum[UnitDensity]",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Density",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee5032f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Density",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0750,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda06c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ec00d7660,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "density": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde85c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ec00d7660,                                                 ),                                             ],                                         },                                         expected_repr: "'density'",                                         name: "literal['density']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['density']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDensity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee168f0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDensity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.density.Density, type: Literal['density'] = 'density') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Density

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Density, required=True), 'type': FieldInfo(annotation=Literal['density'], required=False, default='density')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['density']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionDisableDryRun(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.disable_dry_run.DisableDryRun'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['disable_dry_run']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 487

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionDisableDryRun'>, 'config': {'title': 'OptionDisableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionDisableDryRun'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionDisableDryRun:94394502910880', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.disable_dry_run.DisableDryRun'>, 'config': {'title': 'DisableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.disable_dry_run.DisableDryRun'>>]}, 'ref': 'kittycad.models.disable_dry_run.DisableDryRun:94394494562688', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'DisableDryRun', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'disable_dry_run', 'schema': {'expected': ['disable_dry_run'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDisableDryRun', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DisableDryRun, required=True), 'type': FieldInfo(annotation=Literal['disable_dry_run'], required=False, default='disable_dry_run')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed093a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee513180,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "DisableDryRun",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed5f5f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "disable_dry_run",                                             },                                             expected_py: None,                                             name: "literal['disable_dry_run']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDisableDryRun",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDisableDryRun", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd36df0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36d90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "DisableDryRun",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee513180,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "DisableDryRun",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36c10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36f40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed5f5f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "disable_dry_run": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdea4200,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed5f5f0,                                                 ),                                             ],                                         },                                         expected_repr: "'disable_dry_run'",                                         name: "literal['disable_dry_run']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['disable_dry_run']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDisableDryRun",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed093a0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionDisableDryRun",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.disable_dry_run.DisableDryRun, type: Literal['disable_dry_run'] = 'disable_dry_run') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: DisableDryRun

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=DisableDryRun, required=True), 'type': FieldInfo(annotation=Literal['disable_dry_run'], required=False, default='disable_dry_run')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['disable_dry_run']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEdgeLinesVisible(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.edge_lines_visible.EdgeLinesVisible'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['edge_lines_visible']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 337

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEdgeLinesVisible'>, 'config': {'title': 'OptionEdgeLinesVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEdgeLinesVisible'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEdgeLinesVisible:94394502335824', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.edge_lines_visible.EdgeLinesVisible'>, 'config': {'title': 'EdgeLinesVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.edge_lines_visible.EdgeLinesVisible'>>]}, 'ref': 'kittycad.models.edge_lines_visible.EdgeLinesVisible:94394494644080', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EdgeLinesVisible', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'edge_lines_visible', 'schema': {'expected': ['edge_lines_visible'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEdgeLinesVisible', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EdgeLinesVisible, required=True), 'type': FieldInfo(annotation=Literal['edge_lines_visible'], required=False, default='edge_lines_visible')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec7cd50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee71470,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "edge_lines_visible",                                             },                                             expected_py: None,                                             name: "literal['edge_lines_visible']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee526f70,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EdgeLinesVisible",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEdgeLinesVisible",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEdgeLinesVisible", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34c90,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd355f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EdgeLinesVisible",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee526f70,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EdgeLinesVisible",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34bd0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34de0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee71470,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "edge_lines_visible": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd12b40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee71470,                                                 ),                                             ],                                         },                                         expected_repr: "'edge_lines_visible'",                                         name: "literal['edge_lines_visible']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['edge_lines_visible']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEdgeLinesVisible",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec7cd50,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEdgeLinesVisible",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.edge_lines_visible.EdgeLinesVisible, type: Literal['edge_lines_visible'] = 'edge_lines_visible') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EdgeLinesVisible

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EdgeLinesVisible, required=True), 'type': FieldInfo(annotation=Literal['edge_lines_visible'], required=False, default='edge_lines_visible')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['edge_lines_visible']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEmpty(**data)

An empty response, used for any command that does not explicitly have a response defined here.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['empty']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 137

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEmpty'>, 'config': {'title': 'OptionEmpty'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEmpty'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEmpty:94394502803200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {}, 'schema': {'default': 'empty', 'schema': {'expected': ['empty'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEmpty', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['empty'], required=False, default='empty')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eeceef00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ec256d860,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "empty",                                             },                                             expected_py: None,                                             name: "literal['empty']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionEmpty",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEmpty", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35860,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd35890,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ec256d860,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "empty": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf72080,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ec256d860,                                                 ),                                             ],                                         },                                         expected_repr: "'empty'",                                         name: "literal['empty']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['empty']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEmpty",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eeceef00,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEmpty",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['empty'] = 'empty') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['empty'], required=False, default='empty')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['empty']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEnableDryRun(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.enable_dry_run.EnableDryRun'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['enable_dry_run']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 477

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEnableDryRun'>, 'config': {'title': 'OptionEnableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEnableDryRun'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEnableDryRun:94394502901680', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.enable_dry_run.EnableDryRun'>, 'config': {'title': 'EnableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.enable_dry_run.EnableDryRun'>>]}, 'ref': 'kittycad.models.enable_dry_run.EnableDryRun:94394494662832', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EnableDryRun', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'enable_dry_run', 'schema': {'expected': ['enable_dry_run'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEnableDryRun', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EnableDryRun, required=True), 'type': FieldInfo(annotation=Literal['enable_dry_run'], required=False, default='enable_dry_run')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed06fb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee712f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "enable_dry_run",                                             },                                             expected_py: None,                                             name: "literal['enable_dry_run']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee52b8b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EnableDryRun",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEnableDryRun",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEnableDryRun", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6d60,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6d90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EnableDryRun",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee52b8b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EnableDryRun",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6dc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6df0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee712f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "enable_dry_run": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd58480,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee712f0,                                                 ),                                             ],                                         },                                         expected_repr: "'enable_dry_run'",                                         name: "literal['enable_dry_run']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['enable_dry_run']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEnableDryRun",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed06fb0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEnableDryRun",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.enable_dry_run.EnableDryRun, type: Literal['enable_dry_run'] = 'enable_dry_run') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EnableDryRun

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EnableDryRun, required=True), 'type': FieldInfo(annotation=Literal['enable_dry_run'], required=False, default='enable_dry_run')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['enable_dry_run']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEnableSketchMode(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.enable_sketch_mode.EnableSketchMode'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['enable_sketch_mode']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 507

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEnableSketchMode'>, 'config': {'title': 'OptionEnableSketchMode'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEnableSketchMode'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEnableSketchMode:94394502929472', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.enable_sketch_mode.EnableSketchMode'>, 'config': {'title': 'EnableSketchMode'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.enable_sketch_mode.EnableSketchMode'>>]}, 'ref': 'kittycad.models.enable_sketch_mode.EnableSketchMode:94394494656944', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EnableSketchMode', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'enable_sketch_mode', 'schema': {'expected': ['enable_sketch_mode'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEnableSketchMode', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EnableSketchMode, required=True), 'type': FieldInfo(annotation=Literal['enable_sketch_mode'], required=False, default='enable_sketch_mode')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed0dc40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee52a1b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EnableSketchMode",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee71230,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "enable_sketch_mode",                                             },                                             expected_py: None,                                             name: "literal['enable_sketch_mode']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEnableSketchMode",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEnableSketchMode", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35e00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35ad0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EnableSketchMode",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee52a1b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EnableSketchMode",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35b30,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd35b60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee71230,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "enable_sketch_mode": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd02680,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee71230,                                                 ),                                             ],                                         },                                         expected_repr: "'enable_sketch_mode'",                                         name: "literal['enable_sketch_mode']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['enable_sketch_mode']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEnableSketchMode",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed0dc40,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEnableSketchMode",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.enable_sketch_mode.EnableSketchMode, type: Literal['enable_sketch_mode'] = 'enable_sketch_mode') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EnableSketchMode

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EnableSketchMode, required=True), 'type': FieldInfo(annotation=Literal['enable_sketch_mode'], required=False, default='enable_sketch_mode')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['enable_sketch_mode']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEngineUtilEvaluatePath(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.engine_util_evaluate_path.EngineUtilEvaluatePath'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['engine_util_evaluate_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 145

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEngineUtilEvaluatePath'>, 'config': {'title': 'OptionEngineUtilEvaluatePath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEngineUtilEvaluatePath'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEngineUtilEvaluatePath:94394502799648', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.engine_util_evaluate_path.EngineUtilEvaluatePath'>, 'config': {'title': 'EngineUtilEvaluatePath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.engine_util_evaluate_path.EngineUtilEvaluatePath'>>]}, 'ref': 'kittycad.models.engine_util_evaluate_path.EngineUtilEvaluatePath:94394494654528', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'pos': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'EngineUtilEvaluatePath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'engine_util_evaluate_path', 'schema': {'expected': ['engine_util_evaluate_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEngineUtilEvaluatePath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EngineUtilEvaluatePath, required=True), 'type': FieldInfo(annotation=Literal['engine_util_evaluate_path'], required=False, default='engine_util_evaluate_path')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecee120,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee529840,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "pos": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f05408,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9edd655a0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "x": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08838,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08868,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "z": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08898,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 3,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "Point3d",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EngineUtilEvaluatePath",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee49ed0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "engine_util_evaluate_path",                                             },                                             expected_py: None,                                             name: "literal['engine_util_evaluate_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEngineUtilEvaluatePath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEngineUtilEvaluatePath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34570,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd34960,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "pos",                                                 lookup_key: Simple {                                                     key: "pos",                                                     py_key: Py(                                                         0x00007f1ebdd34540,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "pos",                                                                 Py(                                                                     0x00007f1ebdd34660,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f05408,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "x",                                                                         lookup_key: Simple {                                                                             key: "x",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08838,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "x",                                                                                         Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08838,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "y",                                                                         lookup_key: Simple {                                                                             key: "y",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08868,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "y",                                                                                         Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08868,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "z",                                                                         lookup_key: Simple {                                                                             key: "z",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08898,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "z",                                                                                         Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08898,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "Point3d",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9edd655a0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "Point3d",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EngineUtilEvaluatePath",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee529840,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EngineUtilEvaluatePath",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34750,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34630,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee49ed0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "engine_util_evaluate_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd23500,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee49ed0,                                                 ),                                             ],                                         },                                         expected_repr: "'engine_util_evaluate_path'",                                         name: "literal['engine_util_evaluate_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['engine_util_evaluate_path']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEngineUtilEvaluatePath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecee120,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEngineUtilEvaluatePath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.engine_util_evaluate_path.EngineUtilEvaluatePath, type: Literal['engine_util_evaluate_path'] = 'engine_util_evaluate_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EngineUtilEvaluatePath

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EngineUtilEvaluatePath, required=True), 'type': FieldInfo(annotation=Literal['engine_util_evaluate_path'], required=False, default='engine_util_evaluate_path')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['engine_util_evaluate_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityCircularPattern(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_circular_pattern.EntityCircularPattern'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_circular_pattern']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1331

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityCircularPattern'>, 'config': {'title': 'OptionEntityCircularPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityCircularPattern'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityCircularPattern:94394504132512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_circular_pattern.EntityCircularPattern'>, 'config': {'title': 'EntityCircularPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_circular_pattern.EntityCircularPattern'>>]}, 'ref': 'kittycad.models.entity_circular_pattern.EntityCircularPattern:94394494716096', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityCircularPattern', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_circular_pattern', 'schema': {'expected': ['entity_circular_pattern'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityCircularPattern', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityCircularPattern, required=True), 'type': FieldInfo(annotation=Literal['entity_circular_pattern'], required=False, default='entity_circular_pattern')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee337a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee5388c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityCircularPattern",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70130,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_circular_pattern",                                             },                                             expected_py: None,                                             name: "literal['entity_circular_pattern']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityCircularPattern",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityCircularPattern", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdc08300,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdc08330,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdc062f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdc062b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityCircularPattern",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee5388c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityCircularPattern",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdc08360,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdc08390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70130,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_circular_pattern": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdc06340,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70130,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_circular_pattern'",                                         name: "literal['entity_circular_pattern']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_circular_pattern']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityCircularPattern",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee337a0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityCircularPattern",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_circular_pattern.EntityCircularPattern, type: Literal['entity_circular_pattern'] = 'entity_circular_pattern') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityCircularPattern

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityCircularPattern, required=True), 'type': FieldInfo(annotation=Literal['entity_circular_pattern'], required=False, default='entity_circular_pattern')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_circular_pattern']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityClone(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_clone.EntityClone'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_clone']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1301

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityClone'>, 'config': {'title': 'OptionEntityClone'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityClone'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityClone:94394504099328', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_clone.EntityClone'>, 'config': {'title': 'EntityClone'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_clone.EntityClone'>>]}, 'ref': 'kittycad.models.entity_clone.EntityClone:94394494727904', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntityClone', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_clone', 'schema': {'expected': ['entity_clone'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityClone', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityClone, required=True), 'type': FieldInfo(annotation=Literal['entity_clone'], required=False, default='entity_clone')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee2b600,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee701f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_clone",                                             },                                             expected_py: None,                                             name: "literal['entity_clone']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee53b6e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityClone",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityClone",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityClone", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3840,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3870,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntityClone",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee53b6e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityClone",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda38a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda38d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee701f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_clone": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddf2ec0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee701f0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_clone'",                                         name: "literal['entity_clone']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_clone']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityClone",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee2b600,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityClone",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_clone.EntityClone, type: Literal['entity_clone'] = 'entity_clone') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityClone

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityClone, required=True), 'type': FieldInfo(annotation=Literal['entity_clone'], required=False, default='entity_clone')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_clone']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityFade(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_fade.EntityFade'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_fade']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 417

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityFade'>, 'config': {'title': 'OptionEntityFade'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityFade'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityFade:94394502411200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_fade.EntityFade'>, 'config': {'title': 'EntityFade'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_fade.EntityFade'>>]}, 'ref': 'kittycad.models.entity_fade.EntityFade:94394494726912', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntityFade', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_fade', 'schema': {'expected': ['entity_fade'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityFade', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityFade, required=True), 'type': FieldInfo(annotation=Literal['entity_fade'], required=False, default='entity_fade')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec8f3c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee53b300,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityFade",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee702f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_fade",                                             },                                             expected_py: None,                                             name: "literal['entity_fade']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityFade",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityFade", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5860,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5890,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntityFade",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee53b300,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityFade",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded58c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded58f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee702f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_fade": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd02c00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee702f0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_fade'",                                         name: "literal['entity_fade']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_fade']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityFade",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec8f3c0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityFade",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_fade.EntityFade, type: Literal['entity_fade'] = 'entity_fade') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityFade

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityFade, required=True), 'type': FieldInfo(annotation=Literal['entity_fade'], required=False, default='entity_fade')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_fade']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetAllChildUuids(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_all_child_uuids.EntityGetAllChildUuids'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_all_child_uuids']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 769

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetAllChildUuids'>, 'config': {'title': 'OptionEntityGetAllChildUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetAllChildUuids'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetAllChildUuids:94394503217264', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_all_child_uuids.EntityGetAllChildUuids'>, 'config': {'title': 'EntityGetAllChildUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_all_child_uuids.EntityGetAllChildUuids'>>]}, 'ref': 'kittycad.models.entity_get_all_child_uuids.EntityGetAllChildUuids:94394494733312', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityGetAllChildUuids', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_all_child_uuids', 'schema': {'expected': ['entity_get_all_child_uuids'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetAllChildUuids', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetAllChildUuids, required=True), 'type': FieldInfo(annotation=Literal['entity_get_all_child_uuids'], required=False, default='entity_get_all_child_uuids')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed54070,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee4a010,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_all_child_uuids",                                             },                                             expected_py: None,                                             name: "literal['entity_get_all_child_uuids']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee53cc00,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetAllChildUuids",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetAllChildUuids",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetAllChildUuids", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7750,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7780,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdd826b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdd82670,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetAllChildUuids",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee53cc00,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetAllChildUuids",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded76f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7630,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee4a010,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_all_child_uuids": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd82700,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee4a010,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_all_child_uuids'",                                         name: "literal['entity_get_all_child_uuids']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_all_child_uuids']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetAllChildUuids",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed54070,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetAllChildUuids",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_all_child_uuids.EntityGetAllChildUuids, type: Literal['entity_get_all_child_uuids'] = 'entity_get_all_child_uuids') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetAllChildUuids

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetAllChildUuids, required=True), 'type': FieldInfo(annotation=Literal['entity_get_all_child_uuids'], required=False, default='entity_get_all_child_uuids')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_all_child_uuids']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetChildUuid(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_child_uuid.EntityGetChildUuid'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_child_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 739

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetChildUuid'>, 'config': {'title': 'OptionEntityGetChildUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetChildUuid'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetChildUuid:94394503182944', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_child_uuid.EntityGetChildUuid'>, 'config': {'title': 'EntityGetChildUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_child_uuid.EntityGetChildUuid'>>]}, 'ref': 'kittycad.models.entity_get_child_uuid.EntityGetChildUuid:94394494744496', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'EntityGetChildUuid', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_child_uuid', 'schema': {'expected': ['entity_get_child_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetChildUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetChildUuid, required=True), 'type': FieldInfo(annotation=Literal['entity_get_child_uuid'], required=False, default='entity_get_child_uuid')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed4ba60,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70470,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_child_uuid",                                             },                                             expected_py: None,                                             name: "literal['entity_get_child_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee53f7b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe494bb0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetChildUuid",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetChildUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetChildUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd361c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36280,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_id",                                                 lookup_key: Simple {                                                     key: "entity_id",                                                     py_key: Py(                                                         0x00007f1ebdd775f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_id",                                                                 Py(                                                                     0x00007f1ebdd775b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe494bb0,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetChildUuid",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee53f7b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetChildUuid",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd362b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd360d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70470,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_child_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd77640,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70470,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_child_uuid'",                                         name: "literal['entity_get_child_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_child_uuid']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetChildUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed4ba60,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetChildUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_child_uuid.EntityGetChildUuid, type: Literal['entity_get_child_uuid'] = 'entity_get_child_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetChildUuid

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetChildUuid, required=True), 'type': FieldInfo(annotation=Literal['entity_get_child_uuid'], required=False, default='entity_get_child_uuid')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_child_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetDistance(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_distance.EntityGetDistance'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_distance']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1291

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetDistance'>, 'config': {'title': 'OptionEntityGetDistance'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetDistance'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetDistance:94394504085776', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_distance.EntityGetDistance'>, 'config': {'title': 'EntityGetDistance'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_distance.EntityGetDistance'>>]}, 'ref': 'kittycad.models.entity_get_distance.EntityGetDistance:94394494721504', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'max_distance': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'min_distance': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'EntityGetDistance', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_distance', 'schema': {'expected': ['entity_get_distance'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetDistance', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetDistance, required=True), 'type': FieldInfo(annotation=Literal['entity_get_distance'], required=False, default='entity_get_distance')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee28110,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee539de0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "max_distance": SerField {                                                     key_py: Py(                                                         0x00007f1ec1f843f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "min_distance": SerField {                                                     key_py: Py(                                                         0x00007f1ebe487ef0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetDistance",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee705b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_distance",                                             },                                             expected_py: None,                                             name: "literal['entity_get_distance']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetDistance",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetDistance", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda34e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3510,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "max_distance",                                                 lookup_key: Simple {                                                     key: "max_distance",                                                     py_key: Py(                                                         0x00007f1ebddf1ef0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "max_distance",                                                                 Py(                                                                     0x00007f1ebddf1eb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1f843f0,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055d9ee53edc0,                                                         ),                                                         config: Py(                                                             0x00007f1ebddf1c80,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "min_distance",                                                 lookup_key: Simple {                                                     key: "min_distance",                                                     py_key: Py(                                                         0x00007f1ebddf1f70,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "min_distance",                                                                 Py(                                                                     0x00007f1ebddf1f30,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe487ef0,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055d9ee53edc0,                                                         ),                                                         config: Py(                                                             0x00007f1ebddf1c80,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetDistance",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee539de0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetDistance",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3540,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3570,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee705b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_distance": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddf2000,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee705b0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_distance'",                                         name: "literal['entity_get_distance']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_distance']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetDistance",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee28110,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetDistance",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_distance.EntityGetDistance, type: Literal['entity_get_distance'] = 'entity_get_distance') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetDistance

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetDistance, required=True), 'type': FieldInfo(annotation=Literal['entity_get_distance'], required=False, default='entity_get_distance')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_distance']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetNumChildren(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_num_children.EntityGetNumChildren'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_num_children']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 749

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetNumChildren'>, 'config': {'title': 'OptionEntityGetNumChildren'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetNumChildren'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetNumChildren:94394503194224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_num_children.EntityGetNumChildren'>, 'config': {'title': 'EntityGetNumChildren'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_num_children.EntityGetNumChildren'>>]}, 'ref': 'kittycad.models.entity_get_num_children.EntityGetNumChildren:94394494754320', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'num': {'metadata': {}, 'schema': {'type': 'int'}, 'type': 'model-field'}}, 'model_name': 'EntityGetNumChildren', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_num_children', 'schema': {'expected': ['entity_get_num_children'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetNumChildren', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetNumChildren, required=True), 'type': FieldInfo(annotation=Literal['entity_get_num_children'], required=False, default='entity_get_num_children')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed4e670,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee541e10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "num": SerField {                                                     key_py: Py(                                                         0x00007f1ec25b0150,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Int(                                                             IntSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetNumChildren",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70730,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_num_children",                                             },                                             expected_py: None,                                             name: "literal['entity_get_num_children']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetNumChildren",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetNumChildren", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd36a90,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36ee0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "num",                                                 lookup_key: Simple {                                                     key: "num",                                                     py_key: Py(                                                         0x00007f1ebdd36d30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "num",                                                                 Py(                                                                     0x00007f1ebdd36fa0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec25b0150,                                                 ),                                                 validator: Int(                                                     IntValidator {                                                         strict: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetNumChildren",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee541e10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetNumChildren",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36e20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36cd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70730,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_num_children": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd805c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70730,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_num_children'",                                         name: "literal['entity_get_num_children']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_num_children']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetNumChildren",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed4e670,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetNumChildren",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_num_children.EntityGetNumChildren, type: Literal['entity_get_num_children'] = 'entity_get_num_children') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetNumChildren

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetNumChildren, required=True), 'type': FieldInfo(annotation=Literal['entity_get_num_children'], required=False, default='entity_get_num_children')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_num_children']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetParentId(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_parent_id.EntityGetParentId'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_parent_id']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 759

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetParentId'>, 'config': {'title': 'OptionEntityGetParentId'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetParentId'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetParentId:94394503205872', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_parent_id.EntityGetParentId'>, 'config': {'title': 'EntityGetParentId'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_parent_id.EntityGetParentId'>>]}, 'ref': 'kittycad.models.entity_get_parent_id.EntityGetParentId:94394494767664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'EntityGetParentId', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_parent_id', 'schema': {'expected': ['entity_get_parent_id'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetParentId', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetParentId, required=True), 'type': FieldInfo(annotation=Literal['entity_get_parent_id'], required=False, default='entity_get_parent_id')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed513f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70930,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_parent_id",                                             },                                             expected_py: None,                                             name: "literal['entity_get_parent_id']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee545230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe494bb0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetParentId",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetParentId",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetParentId", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7ba0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_id",                                                 lookup_key: Simple {                                                     key: "entity_id",                                                     py_key: Py(                                                         0x00007f1ebdd815f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_id",                                                                 Py(                                                                     0x00007f1ebdd815b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe494bb0,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetParentId",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee545230,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetParentId",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7bd0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7b70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70930,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_parent_id": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd81640,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70930,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_parent_id'",                                         name: "literal['entity_get_parent_id']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_parent_id']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetParentId",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed513f0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetParentId",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_parent_id.EntityGetParentId, type: Literal['entity_get_parent_id'] = 'entity_get_parent_id') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetParentId

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetParentId, required=True), 'type': FieldInfo(annotation=Literal['entity_get_parent_id'], required=False, default='entity_get_parent_id')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_parent_id']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityGetSketchPaths(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_get_sketch_paths.EntityGetSketchPaths'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_sketch_paths']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 779

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetSketchPaths'>, 'config': {'title': 'OptionEntityGetSketchPaths'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetSketchPaths'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityGetSketchPaths:94394503229552', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_get_sketch_paths.EntityGetSketchPaths'>, 'config': {'title': 'EntityGetSketchPaths'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_get_sketch_paths.EntityGetSketchPaths'>>]}, 'ref': 'kittycad.models.entity_get_sketch_paths.EntityGetSketchPaths:94394494752928', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityGetSketchPaths', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_get_sketch_paths', 'schema': {'expected': ['entity_get_sketch_paths'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetSketchPaths', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetSketchPaths, required=True), 'type': FieldInfo(annotation=Literal['entity_get_sketch_paths'], required=False, default='entity_get_sketch_paths')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed57070,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70af0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_sketch_paths",                                             },                                             expected_py: None,                                             name: "literal['entity_get_sketch_paths']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee5418a0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityGetSketchPaths",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetSketchPaths",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetSketchPaths", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7300,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded72a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdd837b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdd83770,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityGetSketchPaths",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee5418a0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityGetSketchPaths",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7180,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7330,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70af0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_sketch_paths": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd83800,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70af0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_sketch_paths'",                                         name: "literal['entity_get_sketch_paths']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_sketch_paths']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetSketchPaths",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed57070,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityGetSketchPaths",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_get_sketch_paths.EntityGetSketchPaths, type: Literal['entity_get_sketch_paths'] = 'entity_get_sketch_paths') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityGetSketchPaths

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityGetSketchPaths, required=True), 'type': FieldInfo(annotation=Literal['entity_get_sketch_paths'], required=False, default='entity_get_sketch_paths')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_sketch_paths']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPattern(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_linear_pattern.EntityLinearPattern'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_linear_pattern']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1321

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPattern'>, 'config': {'title': 'OptionEntityLinearPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPattern'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPattern:94394504120320', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_linear_pattern.EntityLinearPattern'>, 'config': {'title': 'EntityLinearPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_linear_pattern.EntityLinearPattern'>>]}, 'ref': 'kittycad.models.entity_linear_pattern.EntityLinearPattern:94394494779440', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityLinearPattern', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_linear_pattern', 'schema': {'expected': ['entity_linear_pattern'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityLinearPattern', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityLinearPattern, required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern'], required=False, default='entity_linear_pattern')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee30800,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee548030,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityLinearPattern",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70bf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_linear_pattern",                                             },                                             expected_py: None,                                             name: "literal['entity_linear_pattern']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityLinearPattern",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityLinearPattern", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3f30,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3f60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdc05170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdc05130,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityLinearPattern",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee548030,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityLinearPattern",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3f90,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3fc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70bf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_linear_pattern": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdc051c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70bf0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_linear_pattern'",                                         name: "literal['entity_linear_pattern']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_linear_pattern']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityLinearPattern",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee30800,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityLinearPattern",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_linear_pattern.EntityLinearPattern, type: Literal['entity_linear_pattern'] = 'entity_linear_pattern') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityLinearPattern

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityLinearPattern, required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern'], required=False, default='entity_linear_pattern')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_linear_pattern']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPatternTransform(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_linear_pattern_transform.EntityLinearPatternTransform'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_linear_pattern_transform']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1311

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPatternTransform'>, 'config': {'title': 'OptionEntityLinearPatternTransform'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPatternTransform'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityLinearPatternTransform:94394504108416', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_linear_pattern_transform.EntityLinearPatternTransform'>, 'config': {'title': 'EntityLinearPatternTransform'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_linear_pattern_transform.EntityLinearPatternTransform'>>]}, 'ref': 'kittycad.models.entity_linear_pattern_transform.EntityLinearPatternTransform:94394494787824', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityLinearPatternTransform', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_linear_pattern_transform', 'schema': {'expected': ['entity_linear_pattern_transform'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityLinearPatternTransform', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityLinearPatternTransform, required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern_transform'], required=False, default='entity_linear_pattern_transform')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee2d980,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee4a060,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_linear_pattern_transform",                                             },                                             expected_py: None,                                             name: "literal['entity_linear_pattern_transform']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee54a0f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityLinearPatternTransform",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityLinearPatternTransform",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityLinearPatternTransform", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3ba0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3bd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebddf3fb0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebddf3f70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityLinearPatternTransform",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee54a0f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityLinearPatternTransform",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3c00,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3c30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee4a060,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_linear_pattern_transform": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdc04040,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee4a060,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_linear_pattern_transform'",                                         name: "literal['entity_linear_pattern_transform']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_linear_pattern_transform']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityLinearPatternTransform",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee2d980,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityLinearPatternTransform",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_linear_pattern_transform.EntityLinearPatternTransform, type: Literal['entity_linear_pattern_transform'] = 'entity_linear_pattern_transform') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityLinearPatternTransform

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityLinearPatternTransform, required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern_transform'], required=False, default='entity_linear_pattern_transform')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_linear_pattern_transform']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelix(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_make_helix.EntityMakeHelix'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_make_helix']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1361

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelix'>, 'config': {'title': 'OptionEntityMakeHelix'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelix'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelix:94394504169360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_make_helix.EntityMakeHelix'>, 'config': {'title': 'EntityMakeHelix'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_make_helix.EntityMakeHelix'>>]}, 'ref': 'kittycad.models.entity_make_helix.EntityMakeHelix:94394494793232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntityMakeHelix', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_make_helix', 'schema': {'expected': ['entity_make_helix'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMakeHelix', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelix, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix'], required=False, default='entity_make_helix')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee3c790,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee54b610,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityMakeHelix",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee70fb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_make_helix",                                             },                                             expected_py: None,                                             name: "literal['entity_make_helix']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMakeHelix",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMakeHelix", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda39f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3a50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntityMakeHelix",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee54b610,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityMakeHelix",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3900,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3a20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee70fb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_make_helix": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde2240,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee70fb0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_make_helix'",                                         name: "literal['entity_make_helix']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_make_helix']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMakeHelix",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee3c790,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityMakeHelix",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_make_helix.EntityMakeHelix, type: Literal['entity_make_helix'] = 'entity_make_helix') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityMakeHelix

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelix, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix'], required=False, default='entity_make_helix')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_make_helix']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_make_helix_from_edge.EntityMakeHelixFromEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_make_helix_from_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1381

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromEdge'>, 'config': {'title': 'OptionEntityMakeHelixFromEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromEdge:94394504188176', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_make_helix_from_edge.EntityMakeHelixFromEdge'>, 'config': {'title': 'EntityMakeHelixFromEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_make_helix_from_edge.EntityMakeHelixFromEdge'>>]}, 'ref': 'kittycad.models.entity_make_helix_from_edge.EntityMakeHelixFromEdge:94394494799632', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntityMakeHelixFromEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_make_helix_from_edge', 'schema': {'expected': ['entity_make_helix_from_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMakeHelixFromEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelixFromEdge, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix_from_edge'], required=False, default='entity_make_helix_from_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee41110,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee54cf10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityMakeHelixFromEdge",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee4a150,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_make_helix_from_edge",                                             },                                             expected_py: None,                                             name: "literal['entity_make_helix_from_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMakeHelixFromEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMakeHelixFromEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1740,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda14a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntityMakeHelixFromEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee54cf10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityMakeHelixFromEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1470,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1650,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee4a150,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_make_helix_from_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddf29c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee4a150,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_make_helix_from_edge'",                                         name: "literal['entity_make_helix_from_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_make_helix_from_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMakeHelixFromEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee41110,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityMakeHelixFromEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_make_helix_from_edge.EntityMakeHelixFromEdge, type: Literal['entity_make_helix_from_edge'] = 'entity_make_helix_from_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityMakeHelixFromEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelixFromEdge, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix_from_edge'], required=False, default='entity_make_helix_from_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_make_helix_from_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromParams(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_make_helix_from_params.EntityMakeHelixFromParams'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_make_helix_from_params']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1371

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromParams'>, 'config': {'title': 'OptionEntityMakeHelixFromParams'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromParams'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityMakeHelixFromParams:94394504178848', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_make_helix_from_params.EntityMakeHelixFromParams'>, 'config': {'title': 'EntityMakeHelixFromParams'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_make_helix_from_params.EntityMakeHelixFromParams'>>]}, 'ref': 'kittycad.models.entity_make_helix_from_params.EntityMakeHelixFromParams:94394494806000', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntityMakeHelixFromParams', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_make_helix_from_params', 'schema': {'expected': ['entity_make_helix_from_params'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMakeHelixFromParams', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelixFromParams, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix_from_params'], required=False, default='entity_make_helix_from_params')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee3eca0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee54e7f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityMakeHelixFromParams",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee4a100,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_make_helix_from_params",                                             },                                             expected_py: None,                                             name: "literal['entity_make_helix_from_params']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMakeHelixFromParams",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMakeHelixFromParams", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3480,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3420,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntityMakeHelixFromParams",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee54e7f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityMakeHelixFromParams",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda33f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee4a100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_make_helix_from_params": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbd6c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee4a100,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_make_helix_from_params'",                                         name: "literal['entity_make_helix_from_params']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_make_helix_from_params']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMakeHelixFromParams",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee3eca0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityMakeHelixFromParams",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_make_helix_from_params.EntityMakeHelixFromParams, type: Literal['entity_make_helix_from_params'] = 'entity_make_helix_from_params') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityMakeHelixFromParams

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMakeHelixFromParams, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix_from_params'], required=False, default='entity_make_helix_from_params')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_make_helix_from_params']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityMirror(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_mirror.EntityMirror'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_mirror']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1341

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirror'>, 'config': {'title': 'OptionEntityMirror'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirror'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirror:94394504144816', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_mirror.EntityMirror'>, 'config': {'title': 'EntityMirror'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_mirror.EntityMirror'>>]}, 'ref': 'kittycad.models.entity_mirror.EntityMirror:94394494811408', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityMirror', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_mirror', 'schema': {'expected': ['entity_mirror'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMirror', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMirror, required=True), 'type': FieldInfo(annotation=Literal['entity_mirror'], required=False, default='entity_mirror')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee367b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee54fd10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityMirror",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee65170,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_mirror",                                             },                                             expected_py: None,                                             name: "literal['entity_mirror']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMirror",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMirror", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdc08690,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdc086c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdc07430,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdc073f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityMirror",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee54fd10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityMirror",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdc086f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdc08720,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee65170,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_mirror": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdc07480,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee65170,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_mirror'",                                         name: "literal['entity_mirror']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_mirror']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMirror",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee367b0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityMirror",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_mirror.EntityMirror, type: Literal['entity_mirror'] = 'entity_mirror') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityMirror

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMirror, required=True), 'type': FieldInfo(annotation=Literal['entity_mirror'], required=False, default='entity_mirror')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_mirror']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntityMirrorAcrossEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_mirror_across_edge.EntityMirrorAcrossEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_mirror_across_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1351

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirrorAcrossEdge'>, 'config': {'title': 'OptionEntityMirrorAcrossEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirrorAcrossEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntityMirrorAcrossEdge:94394504157008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_mirror_across_edge.EntityMirrorAcrossEdge'>, 'config': {'title': 'EntityMirrorAcrossEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_mirror_across_edge.EntityMirrorAcrossEdge'>>]}, 'ref': 'kittycad.models.entity_mirror_across_edge.EntityMirrorAcrossEdge:94394494817808', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'EntityMirrorAcrossEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_mirror_across_edge', 'schema': {'expected': ['entity_mirror_across_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMirrorAcrossEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMirrorAcrossEdge, required=True), 'type': FieldInfo(annotation=Literal['entity_mirror_across_edge'], required=False, default='entity_mirror_across_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee39750,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee4a1f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_mirror_across_edge",                                             },                                             expected_py: None,                                             name: "literal['entity_mirror_across_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee551610,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntityMirrorAcrossEdge",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMirrorAcrossEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMirrorAcrossEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3ed0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda3e70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebdc07eb0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebdc07fb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "EntityMirrorAcrossEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee551610,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntityMirrorAcrossEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3e40,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3de0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee4a1f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_mirror_across_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde2880,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee4a1f0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_mirror_across_edge'",                                         name: "literal['entity_mirror_across_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_mirror_across_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMirrorAcrossEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee39750,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntityMirrorAcrossEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_mirror_across_edge.EntityMirrorAcrossEdge, type: Literal['entity_mirror_across_edge'] = 'entity_mirror_across_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntityMirrorAcrossEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntityMirrorAcrossEdge, required=True), 'type': FieldInfo(annotation=Literal['entity_mirror_across_edge'], required=False, default='entity_mirror_across_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_mirror_across_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionEntitySetOpacity(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.entity_set_opacity.EntitySetOpacity'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['entity_set_opacity']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 407

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionEntitySetOpacity'>, 'config': {'title': 'OptionEntitySetOpacity'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionEntitySetOpacity'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionEntitySetOpacity:94394502401744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.entity_set_opacity.EntitySetOpacity'>, 'config': {'title': 'EntitySetOpacity'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.entity_set_opacity.EntitySetOpacity'>>]}, 'ref': 'kittycad.models.entity_set_opacity.EntitySetOpacity:94394494824208', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'EntitySetOpacity', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'entity_set_opacity', 'schema': {'expected': ['entity_set_opacity'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntitySetOpacity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntitySetOpacity, required=True), 'type': FieldInfo(annotation=Literal['entity_set_opacity'], required=False, default='entity_set_opacity')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec8ced0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee552f10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "EntitySetOpacity",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee655b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_set_opacity",                                             },                                             expected_py: None,                                             name: "literal['entity_set_opacity']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntitySetOpacity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntitySetOpacity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded54a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5290,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "EntitySetOpacity",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee552f10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "EntitySetOpacity",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5200,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5260,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee655b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_set_opacity": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd01dc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee655b0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_set_opacity'",                                         name: "literal['entity_set_opacity']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_set_opacity']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntitySetOpacity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec8ced0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionEntitySetOpacity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.entity_set_opacity.EntitySetOpacity, type: Literal['entity_set_opacity'] = 'entity_set_opacity') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: EntitySetOpacity

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=EntitySetOpacity, required=True), 'type': FieldInfo(annotation=Literal['entity_set_opacity'], required=False, default='entity_set_opacity')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_set_opacity']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExport(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.export.Export'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['export']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 709

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExport'>, 'config': {'title': 'OptionExport'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExport'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExport:94394503136976', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.export.Export'>, 'config': {'title': 'Export'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export.Export'>>]}, 'ref': 'kittycad.models.export.Export:94394494895504', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'files': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.export_file.ExportFile'>, 'config': {'title': 'ExportFile'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export_file.ExportFile'>>]}, 'ref': 'kittycad.models.export_file.ExportFile:94394494894512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'contents': {'metadata': {}, 'schema': {'function': {'function': <bound method Base64Data.validate of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'no-info'}, 'schema': {'choices': [{'type': 'str'}, {'type': 'bytes'}], 'type': 'union'}, 'serialization': {'function': <bound method Base64Data.serialize of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'function-plain'}, 'type': 'function-after'}, 'type': 'model-field'}, 'name': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ExportFile', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Export', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'export', 'schema': {'expected': ['export'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExport', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export, required=True), 'type': FieldInfo(annotation=Literal['export'], required=False, default='export')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed406d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ec1844840,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "export",                                             },                                             expected_py: None,                                             name: "literal['export']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee564590,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "files": SerField {                                                     key_py: Py(                                                         0x00007f1ec2912400,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9ee5641b0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "contents": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec28f9e30,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Function(                                                                                                 FunctionPlainSerializer {                                                                                                     func: Py(                                                                                                         0x00007f1ebe45f7c0,                                                                                                     ),                                                                                                     name: "plain_function[serialize]",                                                                                                     function_name: "serialize",                                                                                                     return_serializer: Any(                                                                                                         AnySerializer,                                                                                                     ),                                                                                                     fallback_serializer: None,                                                                                                     when_used: Always,                                                                                                     is_field_serializer: false,                                                                                                     info_arg: false,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "name": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f04968,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Str(                                                                                                 StrSerializer,                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 2,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "ExportFile",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[ExportFile]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Export",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExport",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExport", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a400,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebe142dc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "files",                                                 lookup_key: Simple {                                                     key: "files",                                                     py_key: Py(                                                         0x00007f1ebde9ad30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "files",                                                                 Py(                                                                     0x00007f1ebde996e0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2912400,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "contents",                                                                                     lookup_key: Simple {                                                                                         key: "contents",                                                                                         py_key: Py(                                                                                             0x00007f1ebdd4b130,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "contents",                                                                                                     Py(                                                                                                         0x00007f1ebdd5b270,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec28f9e30,                                                                                     ),                                                                                     validator: FunctionAfter(                                                                                         FunctionAfterValidator {                                                                                             validator: Union(                                                                                                 UnionValidator {                                                                                                     mode: Smart,                                                                                                     choices: [                                                                                                         (                                                                                                             Str(                                                                                                                 StrValidator {                                                                                                                     strict: false,                                                                                                                     coerce_numbers_to_str: false,                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                         (                                                                                                             Bytes(                                                                                                                 BytesValidator {                                                                                                                     strict: false,                                                                                                                     bytes_mode: ValBytesMode {                                                                                                                         ser: Utf8,                                                                                                                     },                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                     ],                                                                                                     custom_error: None,                                                                                                     strict: false,                                                                                                     name: "union[str,bytes]",                                                                                                 },                                                                                             ),                                                                                             func: Py(                                                                                                 0x00007f1ebe45f800,                                                                                             ),                                                                                             config: Py(                                                                                                 0x00007f1ebdd60880,                                                                                             ),                                                                                             name: "function-after[validate(), union[str,bytes]]",                                                                                             field_name: None,                                                                                             info_arg: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "name",                                                                                     lookup_key: Simple {                                                                                         key: "name",                                                                                         py_key: Py(                                                                                             0x00007f1ebde99da0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "name",                                                                                                     Py(                                                                                                         0x00007f1ebde99dd0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f04968,                                                                                     ),                                                                                     validator: Str(                                                                                         StrValidator {                                                                                             strict: false,                                                                                             coerce_numbers_to_str: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "ExportFile",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9ee5641b0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "ExportFile",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Export",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee564590,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Export",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebeb67360,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebeb64f30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ec1844840,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "export": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd5a300,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ec1844840,                                                 ),                                             ],                                         },                                         expected_repr: "'export'",                                         name: "literal['export']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['export']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExport",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed406d0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExport",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.export.Export, type: Literal['export'] = 'export') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Export

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export, required=True), 'type': FieldInfo(annotation=Literal['export'], required=False, default='export')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['export']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExport2D(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.export2d.Export2d'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['export2d']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 689

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExport2D'>, 'config': {'title': 'OptionExport2D'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExport2D'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExport2D:94394503099968', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.export2d.Export2d'>, 'config': {'title': 'Export2d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export2d.Export2d'>>]}, 'ref': 'kittycad.models.export2d.Export2d:94394494923712', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'files': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.export_file.ExportFile'>, 'config': {'title': 'ExportFile'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export_file.ExportFile'>>]}, 'ref': 'kittycad.models.export_file.ExportFile:94394494894512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'contents': {'metadata': {}, 'schema': {'function': {'function': <bound method Base64Data.validate of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'no-info'}, 'schema': {'choices': [{'type': 'str'}, {'type': 'bytes'}], 'type': 'union'}, 'serialization': {'function': <bound method Base64Data.serialize of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'function-plain'}, 'type': 'function-after'}, 'type': 'model-field'}, 'name': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ExportFile', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Export2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'export2d', 'schema': {'expected': ['export2d'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExport2D', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export2d, required=True), 'type': FieldInfo(annotation=Literal['export2d'], required=False, default='export2d')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed37640,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee56b3c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "files": SerField {                                                     key_py: Py(                                                         0x00007f1ec2912400,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9ee5641b0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "contents": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec28f9e30,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Function(                                                                                                 FunctionPlainSerializer {                                                                                                     func: Py(                                                                                                         0x00007f1ebe45f7c0,                                                                                                     ),                                                                                                     name: "plain_function[serialize]",                                                                                                     function_name: "serialize",                                                                                                     return_serializer: Any(                                                                                                         AnySerializer,                                                                                                     ),                                                                                                     fallback_serializer: None,                                                                                                     when_used: Always,                                                                                                     is_field_serializer: false,                                                                                                     info_arg: false,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "name": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f04968,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Str(                                                                                                 StrSerializer,                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 2,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "ExportFile",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[ExportFile]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Export2d",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66430,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "export2d",                                             },                                             expected_py: None,                                             name: "literal['export2d']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExport2D",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExport2D", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a3d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9a040,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "files",                                                 lookup_key: Simple {                                                     key: "files",                                                     py_key: Py(                                                         0x00007f1ebde99ef0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "files",                                                                 Py(                                                                     0x00007f1ebde99ad0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2912400,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "contents",                                                                                     lookup_key: Simple {                                                                                         key: "contents",                                                                                         py_key: Py(                                                                                             0x00007f1ebe0aa8f0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "contents",                                                                                                     Py(                                                                                                         0x00007f1ebdf1adb0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec28f9e30,                                                                                     ),                                                                                     validator: FunctionAfter(                                                                                         FunctionAfterValidator {                                                                                             validator: Union(                                                                                                 UnionValidator {                                                                                                     mode: Smart,                                                                                                     choices: [                                                                                                         (                                                                                                             Str(                                                                                                                 StrValidator {                                                                                                                     strict: false,                                                                                                                     coerce_numbers_to_str: false,                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                         (                                                                                                             Bytes(                                                                                                                 BytesValidator {                                                                                                                     strict: false,                                                                                                                     bytes_mode: ValBytesMode {                                                                                                                         ser: Utf8,                                                                                                                     },                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                     ],                                                                                                     custom_error: None,                                                                                                     strict: false,                                                                                                     name: "union[str,bytes]",                                                                                                 },                                                                                             ),                                                                                             func: Py(                                                                                                 0x00007f1ebe45f800,                                                                                             ),                                                                                             config: Py(                                                                                                 0x00007f1ebdd02c80,                                                                                             ),                                                                                             name: "function-after[validate(), union[str,bytes]]",                                                                                             field_name: None,                                                                                             info_arg: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "name",                                                                                     lookup_key: Simple {                                                                                         key: "name",                                                                                         py_key: Py(                                                                                             0x00007f1ebde9bea0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "name",                                                                                                     Py(                                                                                                         0x00007f1ebde998c0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f04968,                                                                                     ),                                                                                     validator: Str(                                                                                         StrValidator {                                                                                             strict: false,                                                                                             coerce_numbers_to_str: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "ExportFile",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9ee5641b0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "ExportFile",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Export2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee56b3c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Export2d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde99fb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9a1f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66430,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "export2d": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebe0d16c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66430,                                                 ),                                             ],                                         },                                         expected_repr: "'export2d'",                                         name: "literal['export2d']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['export2d']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExport2D",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed37640,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExport2D",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.export2d.Export2d, type: Literal['export2d'] = 'export2d') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Export2d

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export2d, required=True), 'type': FieldInfo(annotation=Literal['export2d'], required=False, default='export2d')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['export2d']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExport3D(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.export3d.Export3d'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['export3d']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 699

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExport3D'>, 'config': {'title': 'OptionExport3D'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExport3D'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExport3D:94394503118592', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.export3d.Export3d'>, 'config': {'title': 'Export3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export3d.Export3d'>>]}, 'ref': 'kittycad.models.export3d.Export3d:94394494919360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'files': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.export_file.ExportFile'>, 'config': {'title': 'ExportFile'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export_file.ExportFile'>>]}, 'ref': 'kittycad.models.export_file.ExportFile:94394494894512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'contents': {'metadata': {}, 'schema': {'function': {'function': <bound method Base64Data.validate of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'no-info'}, 'schema': {'choices': [{'type': 'str'}, {'type': 'bytes'}], 'type': 'union'}, 'serialization': {'function': <bound method Base64Data.serialize of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'function-plain'}, 'type': 'function-after'}, 'type': 'model-field'}, 'name': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ExportFile', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Export3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'export3d', 'schema': {'expected': ['export3d'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExport3D', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export3d, required=True), 'type': FieldInfo(annotation=Literal['export3d'], required=False, default='export3d')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed3bf00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee67ef0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "export3d",                                             },                                             expected_py: None,                                             name: "literal['export3d']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee56a2c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "files": SerField {                                                     key_py: Py(                                                         0x00007f1ec2912400,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9ee5641b0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "name": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f04968,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Str(                                                                                                 StrSerializer,                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "contents": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec28f9e30,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Function(                                                                                                 FunctionPlainSerializer {                                                                                                     func: Py(                                                                                                         0x00007f1ebe45f7c0,                                                                                                     ),                                                                                                     name: "plain_function[serialize]",                                                                                                     function_name: "serialize",                                                                                                     return_serializer: Any(                                                                                                         AnySerializer,                                                                                                     ),                                                                                                     fallback_serializer: None,                                                                                                     when_used: Always,                                                                                                     is_field_serializer: false,                                                                                                     info_arg: false,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 2,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "ExportFile",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[ExportFile]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Export3d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExport3D",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExport3D", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a700,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9aa90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "files",                                                 lookup_key: Simple {                                                     key: "files",                                                     py_key: Py(                                                         0x00007f1ebde9b4b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "files",                                                                 Py(                                                                     0x00007f1ebde9b3c0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2912400,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "contents",                                                                                     lookup_key: Simple {                                                                                         key: "contents",                                                                                         py_key: Py(                                                                                             0x00007f1ebdd692b0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "contents",                                                                                                     Py(                                                                                                         0x00007f1ebdd693f0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec28f9e30,                                                                                     ),                                                                                     validator: FunctionAfter(                                                                                         FunctionAfterValidator {                                                                                             validator: Union(                                                                                                 UnionValidator {                                                                                                     mode: Smart,                                                                                                     choices: [                                                                                                         (                                                                                                             Str(                                                                                                                 StrValidator {                                                                                                                     strict: false,                                                                                                                     coerce_numbers_to_str: false,                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                         (                                                                                                             Bytes(                                                                                                                 BytesValidator {                                                                                                                     strict: false,                                                                                                                     bytes_mode: ValBytesMode {                                                                                                                         ser: Utf8,                                                                                                                     },                                                                                                                 },                                                                                                             ),                                                                                                             None,                                                                                                         ),                                                                                                     ],                                                                                                     custom_error: None,                                                                                                     strict: false,                                                                                                     name: "union[str,bytes]",                                                                                                 },                                                                                             ),                                                                                             func: Py(                                                                                                 0x00007f1ebe45f800,                                                                                             ),                                                                                             config: Py(                                                                                                 0x00007f1ebdd6a040,                                                                                             ),                                                                                             name: "function-after[validate(), union[str,bytes]]",                                                                                             field_name: None,                                                                                             info_arg: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "name",                                                                                     lookup_key: Simple {                                                                                         key: "name",                                                                                         py_key: Py(                                                                                             0x00007f1ebde9b1e0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "name",                                                                                                     Py(                                                                                                         0x00007f1ebde9ae20,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f04968,                                                                                     ),                                                                                     validator: Str(                                                                                         StrValidator {                                                                                             strict: false,                                                                                             coerce_numbers_to_str: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "ExportFile",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9ee5641b0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "ExportFile",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Export3d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee56a2c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Export3d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b420,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9a0d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee67ef0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "export3d": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd68cc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee67ef0,                                                 ),                                             ],                                         },                                         expected_repr: "'export3d'",                                         name: "literal['export3d']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['export3d']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExport3D",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed3bf00,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExport3D",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.export3d.Export3d, type: Literal['export3d'] = 'export3d') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Export3d

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Export3d, required=True), 'type': FieldInfo(annotation=Literal['export3d'], required=False, default='export3d')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['export3d']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExtendPath(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.extend_path.ExtendPath'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['extend_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 175

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExtendPath'>, 'config': {'title': 'OptionExtendPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExtendPath'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExtendPath:94394494626544', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.extend_path.ExtendPath'>, 'config': {'title': 'ExtendPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.extend_path.ExtendPath'>>]}, 'ref': 'kittycad.models.extend_path.ExtendPath:94394494945168', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'ExtendPath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'extend_path', 'schema': {'expected': ['extend_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExtendPath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ExtendPath, required=True), 'type': FieldInfo(annotation=Literal['extend_path'], required=False, default='extend_path')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9ee522af0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee570790,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ExtendPath",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf66ed30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "extend_path",                                             },                                             expected_py: None,                                             name: "literal['extend_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExtendPath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExtendPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd354a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "ExtendPath",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee570790,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ExtendPath",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35320,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf66ed30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "extend_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd20ac0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf66ed30,                                                 ),                                             ],                                         },                                         expected_repr: "'extend_path'",                                         name: "literal['extend_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['extend_path']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExtendPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9ee522af0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExtendPath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.extend_path.ExtendPath, type: Literal['extend_path'] = 'extend_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ExtendPath

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ExtendPath, required=True), 'type': FieldInfo(annotation=Literal['extend_path'], required=False, default='extend_path')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['extend_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExtrude(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.extrude.Extrude'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['extrude']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 185

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExtrude'>, 'config': {'title': 'OptionExtrude'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExtrude'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExtrude:94394499025552', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.extrude.Extrude'>, 'config': {'title': 'Extrude'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.extrude.Extrude'>>]}, 'ref': 'kittycad.models.extrude.Extrude:94394495070688', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Extrude', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'extrude', 'schema': {'expected': ['extrude'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExtrude', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Extrude, required=True), 'type': FieldInfo(annotation=Literal['extrude'], required=False, default='extrude')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9ee954a90,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf267450,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "extrude",                                             },                                             expected_py: None,                                             name: "literal['extrude']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee58f1e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Extrude",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExtrude",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExtrude", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd352f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde999e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Extrude",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee58f1e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Extrude",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9bde0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9bf90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf267450,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "extrude": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1fc80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf267450,                                                 ),                                             ],                                         },                                         expected_repr: "'extrude'",                                         name: "literal['extrude']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['extrude']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExtrude",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9ee954a90,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExtrude",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.extrude.Extrude, type: Literal['extrude'] = 'extrude') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Extrude

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Extrude, required=True), 'type': FieldInfo(annotation=Literal['extrude'], required=False, default='extrude')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['extrude']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionExtrusionFaceInfo(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['extrusion_face_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1401

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionExtrusionFaceInfo'>, 'config': {'title': 'OptionExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionExtrusionFaceInfo:94394504219200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo'>, 'config': {'title': 'ExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo:94394495105664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'cap': {'metadata': {}, 'schema': {'cls': <enum 'ExtrusionFaceCapType'>, 'members': [ExtrusionFaceCapType.NONE, ExtrusionFaceCapType.TOP, ExtrusionFaceCapType.BOTTOM, ExtrusionFaceCapType.BOTH], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.extrusion_face_cap_type.ExtrusionFaceCapType:94394495082704', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'curve_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'face_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'ExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'extrusion_face_info', 'schema': {'expected': ['extrusion_face_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ExtrusionFaceInfo, required=True), 'type': FieldInfo(annotation=Literal['extrusion_face_info'], required=False, default='extrusion_face_info')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee48a40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee597a80,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "cap": SerField {                                                     key_py: Py(                                                         0x00007f1ec0b2f8a0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee5920d0,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "curve_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe437bf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "face_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebeddda10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 3,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ExtrusionFaceInfo",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee67a30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "extrusion_face_info",                                             },                                             expected_py: None,                                             name: "literal['extrusion_face_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionExtrusionFaceInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExtrusionFaceInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda27c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda27f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "cap",                                                 lookup_key: Simple {                                                     key: "cap",                                                     py_key: Py(                                                         0x00007f1ebdda2790,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "cap",                                                                 Py(                                                                     0x00007f1ebdda25e0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec0b2f8a0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee5920d0,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "bottom": 2,                                                                     "none": 0,                                                                     "both": 3,                                                                     "top": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdf31b40,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe43c230,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe43c170,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe43c290,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe43c2f0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'none', 'top', 'bottom' or 'both'",                                                         strict: false,                                                         class_repr: "ExtrusionFaceCapType",                                                         name: "str-enum[ExtrusionFaceCapType]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "curve_id",                                                 lookup_key: Simple {                                                     key: "curve_id",                                                     py_key: Py(                                                         0x00007f1ebdf33d30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "curve_id",                                                                 Py(                                                                     0x00007f1ebdf32af0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe437bf0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "face_id",                                                 lookup_key: Simple {                                                     key: "face_id",                                                     py_key: Py(                                                         0x00007f1ebdda2490,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "face_id",                                                                 Py(                                                                     0x00007f1ebdda2400,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeddda10,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ExtrusionFaceInfo",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee597a80,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ExtrusionFaceInfo",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2b20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda2ac0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee67a30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "extrusion_face_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf32e00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee67a30,                                                 ),                                             ],                                         },                                         expected_repr: "'extrusion_face_info'",                                         name: "literal['extrusion_face_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['extrusion_face_info']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExtrusionFaceInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee48a40,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionExtrusionFaceInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.extrusion_face_info.ExtrusionFaceInfo, type: Literal['extrusion_face_info'] = 'extrusion_face_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ExtrusionFaceInfo

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ExtrusionFaceInfo, required=True), 'type': FieldInfo(annotation=Literal['extrusion_face_info'], required=False, default='extrusion_face_info')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['extrusion_face_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionFaceGetCenter(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.face_get_center.FaceGetCenter'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['face_get_center']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1181

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetCenter'>, 'config': {'title': 'OptionFaceGetCenter'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetCenter'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetCenter:94394503914000', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.face_get_center.FaceGetCenter'>, 'config': {'title': 'FaceGetCenter'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.face_get_center.FaceGetCenter'>>]}, 'ref': 'kittycad.models.face_get_center.FaceGetCenter:94394495103344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'pos': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'FaceGetCenter', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'face_get_center', 'schema': {'expected': ['face_get_center'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetCenter', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetCenter, required=True), 'type': FieldInfo(annotation=Literal['face_get_center'], required=False, default='face_get_center')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedfe210,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee597170,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "pos": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f05408,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9edd655a0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08868,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "z": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08898,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "x": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08838,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 3,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "Point3d",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "FaceGetCenter",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee67970,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_center",                                             },                                             expected_py: None,                                             name: "literal['face_get_center']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetCenter",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetCenter", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9ac40,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde99d70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "pos",                                                 lookup_key: Simple {                                                     key: "pos",                                                     py_key: Py(                                                         0x00007f1ebde9ab80,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "pos",                                                                 Py(                                                                     0x00007f1ebde9b630,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f05408,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "x",                                                                         lookup_key: Simple {                                                                             key: "x",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08838,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "x",                                                                                         Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08838,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "y",                                                                         lookup_key: Simple {                                                                             key: "y",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08868,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "y",                                                                                         Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08868,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "z",                                                                         lookup_key: Simple {                                                                             key: "z",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08898,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "z",                                                                                         Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08898,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "Point3d",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9edd655a0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "Point3d",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "FaceGetCenter",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee597170,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "FaceGetCenter",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b990,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9abb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee67970,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_center": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf31640,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee67970,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_center'",                                         name: "literal['face_get_center']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_center']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetCenter",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedfe210,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionFaceGetCenter",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.face_get_center.FaceGetCenter, type: Literal['face_get_center'] = 'face_get_center') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: FaceGetCenter

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetCenter, required=True), 'type': FieldInfo(annotation=Literal['face_get_center'], required=False, default='face_get_center')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_center']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionFaceGetGradient(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.face_get_gradient.FaceGetGradient'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['face_get_gradient']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1191

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetGradient'>, 'config': {'title': 'OptionFaceGetGradient'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetGradient'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetGradient:94394503929856', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.face_get_gradient.FaceGetGradient'>, 'config': {'title': 'FaceGetGradient'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.face_get_gradient.FaceGetGradient'>>]}, 'ref': 'kittycad.models.face_get_gradient.FaceGetGradient:94394495124128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'df_du': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'df_dv': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'normal': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'FaceGetGradient', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'face_get_gradient', 'schema': {'expected': ['face_get_gradient'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetGradient', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetGradient, required=True), 'type': FieldInfo(annotation=Literal['face_get_gradient'], required=False, default='face_get_gradient')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee02000,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee678b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_gradient",                                             },                                             expected_py: None,                                             name: "literal['face_get_gradient']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee59c2a0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "df_du": SerField {                                                     key_py: Py(                                                         0x00007f1ebec00f60,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "df_dv": SerField {                                                     key_py: Py(                                                         0x00007f1ebec02940,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "normal": SerField {                                                     key_py: Py(                                                         0x00007f1ec1753240,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 3,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "FaceGetGradient",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetGradient",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetGradient", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd357a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd37420,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "df_du",                                                 lookup_key: Simple {                                                     key: "df_du",                                                     py_key: Py(                                                         0x00007f1ebe141890,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "df_du",                                                                 Py(                                                                     0x00007f1ebe142e50,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebec00f60,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "df_dv",                                                 lookup_key: Simple {                                                     key: "df_dv",                                                     py_key: Py(                                                         0x00007f1ebdd36a60,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "df_dv",                                                                 Py(                                                                     0x00007f1ebdd35740,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebec02940,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "normal",                                                 lookup_key: Simple {                                                     key: "normal",                                                     py_key: Py(                                                         0x00007f1ebdd357d0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "normal",                                                                 Py(                                                                     0x00007f1ebdd35770,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1753240,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "FaceGetGradient",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee59c2a0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "FaceGetGradient",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36e80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36670,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee678b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_gradient": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf6a200,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee678b0,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_gradient'",                                         name: "literal['face_get_gradient']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_gradient']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetGradient",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee02000,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionFaceGetGradient",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.face_get_gradient.FaceGetGradient, type: Literal['face_get_gradient'] = 'face_get_gradient') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: FaceGetGradient

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetGradient, required=True), 'type': FieldInfo(annotation=Literal['face_get_gradient'], required=False, default='face_get_gradient')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_gradient']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionFaceGetPosition(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.face_get_position.FaceGetPosition'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['face_get_position']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1171

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetPosition'>, 'config': {'title': 'OptionFaceGetPosition'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetPosition'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionFaceGetPosition:94394503898144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.face_get_position.FaceGetPosition'>, 'config': {'title': 'FaceGetPosition'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.face_get_position.FaceGetPosition'>>]}, 'ref': 'kittycad.models.face_get_position.FaceGetPosition:94394495121792', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'pos': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'FaceGetPosition', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'face_get_position', 'schema': {'expected': ['face_get_position'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetPosition', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetPosition, required=True), 'type': FieldInfo(annotation=Literal['face_get_position'], required=False, default='face_get_position')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedfa420,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee59b980,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "pos": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f05408,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9edd655a0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08868,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "x": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08838,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "z": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f08898,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Float(                                                                                         FloatSerializer {                                                                                             inf_nan_mode: Null,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 3,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "Point3d",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "FaceGetPosition",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee677f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_position",                                             },                                             expected_py: None,                                             name: "literal['face_get_position']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetPosition",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetPosition", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda31b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda31e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "pos",                                                 lookup_key: Simple {                                                     key: "pos",                                                     py_key: Py(                                                         0x00007f1ebdda3150,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "pos",                                                                 Py(                                                                     0x00007f1ebdda3180,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f05408,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "x",                                                                         lookup_key: Simple {                                                                             key: "x",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08838,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "x",                                                                                         Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08838,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "y",                                                                         lookup_key: Simple {                                                                             key: "y",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08868,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "y",                                                                                         Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08868,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "z",                                                                         lookup_key: Simple {                                                                             key: "z",                                                                             py_key: Py(                                                                                 0x00007f1ec2f08898,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "z",                                                                                         Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f08898,                                                                         ),                                                                         validator: Float(                                                                             FloatValidator {                                                                                 strict: false,                                                                                 allow_inf_nan: true,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "Point3d",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9edd655a0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "Point3d",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "FaceGetPosition",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee59b980,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "FaceGetPosition",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda3210,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda3240,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee677f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_position": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde4e80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee677f0,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_position'",                                         name: "literal['face_get_position']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_position']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetPosition",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedfa420,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionFaceGetPosition",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.face_get_position.FaceGetPosition, type: Literal['face_get_position'] = 'face_get_position') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: FaceGetPosition

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceGetPosition, required=True), 'type': FieldInfo(annotation=Literal['face_get_position'], required=False, default='face_get_position')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_position']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionFaceIsPlanar(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.face_is_planar.FaceIsPlanar'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['face_is_planar']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1161

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceIsPlanar'>, 'config': {'title': 'OptionFaceIsPlanar'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionFaceIsPlanar'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionFaceIsPlanar:94394503869296', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.face_is_planar.FaceIsPlanar'>, 'config': {'title': 'FaceIsPlanar'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.face_is_planar.FaceIsPlanar'>>]}, 'ref': 'kittycad.models.face_is_planar.FaceIsPlanar:94394495149648', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'origin': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'x_axis': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'y_axis': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'z_axis': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'FaceIsPlanar', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'face_is_planar', 'schema': {'expected': ['face_is_planar'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceIsPlanar', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceIsPlanar, required=True), 'type': FieldInfo(annotation=Literal['face_is_planar'], required=False, default='face_is_planar')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedf3370,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee5a2650,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb64f60,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb654d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "z_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb652c0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "origin": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f050a8,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 4,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "FaceIsPlanar",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee67770,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_is_planar",                                             },                                             expected_py: None,                                             name: "literal['face_is_planar']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceIsPlanar",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceIsPlanar", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2e20,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2e50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "origin",                                                 lookup_key: Simple {                                                     key: "origin",                                                     py_key: Py(                                                         0x00007f1ebdda2ca0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "origin",                                                                 Py(                                                                     0x00007f1ebdda2cd0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f050a8,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: DefinitionRef(                                                                     DefinitionRefValidator {                                                                         definition: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "x_axis",                                                 lookup_key: Simple {                                                     key: "x_axis",                                                     py_key: Py(                                                         0x00007f1ebdda2d00,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x_axis",                                                                 Py(                                                                     0x00007f1ebdda2d30,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb654d0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: DefinitionRef(                                                                     DefinitionRefValidator {                                                                         definition: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y_axis",                                                 lookup_key: Simple {                                                     key: "y_axis",                                                     py_key: Py(                                                         0x00007f1ebdda2d60,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y_axis",                                                                 Py(                                                                     0x00007f1ebdda2d90,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb64f60,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: DefinitionRef(                                                                     DefinitionRefValidator {                                                                         definition: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z_axis",                                                 lookup_key: Simple {                                                     key: "z_axis",                                                     py_key: Py(                                                         0x00007f1ebdda2dc0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z_axis",                                                                 Py(                                                                     0x00007f1ebdda2df0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb652c0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: DefinitionRef(                                                                     DefinitionRefValidator {                                                                         definition: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "FaceIsPlanar",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee5a2650,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "FaceIsPlanar",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2e80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda2eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee67770,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_is_planar": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde38c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee67770,                                                 ),                                             ],                                         },                                         expected_repr: "'face_is_planar'",                                         name: "literal['face_is_planar']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_is_planar']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceIsPlanar",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedf3370,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionFaceIsPlanar",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.face_is_planar.FaceIsPlanar, type: Literal['face_is_planar'] = 'face_is_planar') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: FaceIsPlanar

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=FaceIsPlanar, required=True), 'type': FieldInfo(annotation=Literal['face_is_planar'], required=False, default='face_is_planar')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_is_planar']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionGetEntityType(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.get_entity_type.GetEntityType'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['get_entity_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1019

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionGetEntityType'>, 'config': {'title': 'OptionGetEntityType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionGetEntityType'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionGetEntityType:94394500565632', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.get_entity_type.GetEntityType'>, 'config': {'title': 'GetEntityType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.get_entity_type.GetEntityType'>>]}, 'ref': 'kittycad.models.get_entity_type.GetEntityType:94394495544864', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_type': {'metadata': {}, 'schema': {'cls': <enum 'EntityType'>, 'members': [EntityType.ENTITY, EntityType.OBJECT, EntityType.PATH, EntityType.CURVE, EntityType.SOLID2D, EntityType.SOLID3D, EntityType.EDGE, EntityType.FACE, EntityType.PLANE, EntityType.VERTEX], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.entity_type.EntityType:94394494836016', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'GetEntityType', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'get_entity_type', 'schema': {'expected': ['get_entity_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetEntityType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetEntityType, required=True), 'type': FieldInfo(annotation=Literal['get_entity_type'], required=False, default='get_entity_type')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eeacca80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66f30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_entity_type",                                             },                                             expected_py: None,                                             name: "literal['get_entity_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee602e20,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_type": SerField {                                                     key_py: Py(                                                         0x00007f1ebee66270,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee555d30,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "GetEntityType",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetEntityType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetEntityType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6bb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded68e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_type",                                                 lookup_key: Simple {                                                     key: "entity_type",                                                     py_key: Py(                                                         0x00007f1ebddc8630,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_type",                                                                 Py(                                                                     0x00007f1ebddc86f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebee66270,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee555d30,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "solid3d": 5,                                                                     "solid2d": 4,                                                                     "curve": 3,                                                                     "edge": 6,                                                                     "plane": 8,                                                                     "object": 1,                                                                     "vertex": 9,                                                                     "face": 7,                                                                     "path": 2,                                                                     "entity": 0,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebddc8780,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe4a6390,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a65d0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a6630,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a6690,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a66f0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a6750,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a67b0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a6810,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a6870,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe4a68d0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'entity', 'object', 'path', 'curve', 'solid2d', 'solid3d', 'edge', 'face', 'plane' or 'vertex'",                                                         strict: false,                                                         class_repr: "EntityType",                                                         name: "str-enum[EntityType]",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "GetEntityType",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee602e20,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "GetEntityType",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6940,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6760,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66f30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_entity_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddc8540,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66f30,                                                 ),                                             ],                                         },                                         expected_repr: "'get_entity_type'",                                         name: "literal['get_entity_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_entity_type']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetEntityType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eeacca80,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionGetEntityType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.get_entity_type.GetEntityType, type: Literal['get_entity_type'] = 'get_entity_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: GetEntityType

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetEntityType, required=True), 'type': FieldInfo(annotation=Literal['get_entity_type'], required=False, default='get_entity_type')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_entity_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionGetNumObjects(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.get_num_objects.GetNumObjects'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['get_num_objects']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 899

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionGetNumObjects'>, 'config': {'title': 'OptionGetNumObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionGetNumObjects'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionGetNumObjects:94394503557200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.get_num_objects.GetNumObjects'>, 'config': {'title': 'GetNumObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.get_num_objects.GetNumObjects'>>]}, 'ref': 'kittycad.models.get_num_objects.GetNumObjects:94394495569728', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'num_objects': {'metadata': {}, 'schema': {'type': 'int'}, 'type': 'model-field'}}, 'model_name': 'GetNumObjects', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'get_num_objects', 'schema': {'expected': ['get_num_objects'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetNumObjects', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetNumObjects, required=True), 'type': FieldInfo(annotation=Literal['get_num_objects'], required=False, default='get_num_objects')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eeda7050,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee608f40,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "num_objects": SerField {                                                     key_py: Py(                                                         0x00007f1ebf6c94f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Int(                                                             IntSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "GetNumObjects",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66eb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_num_objects",                                             },                                             expected_py: None,                                             name: "literal['get_num_objects']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetNumObjects",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetNumObjects", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9b1b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9b0c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "num_objects",                                                 lookup_key: Simple {                                                     key: "num_objects",                                                     py_key: Py(                                                         0x00007f1ebddbcaf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "num_objects",                                                                 Py(                                                                     0x00007f1ebddbcab0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf6c94f0,                                                 ),                                                 validator: Int(                                                     IntValidator {                                                         strict: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "GetNumObjects",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee608f40,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "GetNumObjects",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9afd0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9b090,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66eb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_num_objects": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbcb40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66eb0,                                                 ),                                             ],                                         },                                         expected_repr: "'get_num_objects'",                                         name: "literal['get_num_objects']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_num_objects']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetNumObjects",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eeda7050,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionGetNumObjects",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.get_num_objects.GetNumObjects, type: Literal['get_num_objects'] = 'get_num_objects') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: GetNumObjects

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetNumObjects, required=True), 'type': FieldInfo(annotation=Literal['get_num_objects'], required=False, default='get_num_objects')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_num_objects']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionGetSketchModePlane(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.get_sketch_mode_plane.GetSketchModePlane'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['get_sketch_mode_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1281

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionGetSketchModePlane'>, 'config': {'title': 'OptionGetSketchModePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionGetSketchModePlane'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionGetSketchModePlane:94394504063360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.get_sketch_mode_plane.GetSketchModePlane'>, 'config': {'title': 'GetSketchModePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.get_sketch_mode_plane.GetSketchModePlane'>>]}, 'ref': 'kittycad.models.get_sketch_mode_plane.GetSketchModePlane:94394495576128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'origin': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'x_axis': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'y_axis': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'z_axis': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'GetSketchModePlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'get_sketch_mode_plane', 'schema': {'expected': ['get_sketch_mode_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetSketchModePlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetSketchModePlane, required=True), 'type': FieldInfo(annotation=Literal['get_sketch_mode_plane'], required=False, default='get_sketch_mode_plane')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee22980,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee60a840,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb654d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "origin": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f050a8,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb64f60,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "z_axis": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb652c0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Recursive(                                                             DefinitionRefSerializer {                                                                 definition: "...",                                                                 retry_with_lax_check: true,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 4,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "GetSketchModePlane",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66df0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_sketch_mode_plane",                                             },                                             expected_py: None,                                             name: "literal['get_sketch_mode_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetSketchModePlane",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetSketchModePlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1cb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2070,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "origin",                                                 lookup_key: Simple {                                                     key: "origin",                                                     py_key: Py(                                                         0x00007f1ebdda1bc0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "origin",                                                                 Py(                                                                     0x00007f1ebdda1bf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f050a8,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "x_axis",                                                 lookup_key: Simple {                                                     key: "x_axis",                                                     py_key: Py(                                                         0x00007f1ebdda1c20,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x_axis",                                                                 Py(                                                                     0x00007f1ebdda1c50,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb654d0,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y_axis",                                                 lookup_key: Simple {                                                     key: "y_axis",                                                     py_key: Py(                                                         0x00007f1ebdda1c80,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y_axis",                                                                 Py(                                                                     0x00007f1ebdda1ef0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb64f60,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z_axis",                                                 lookup_key: Simple {                                                     key: "z_axis",                                                     py_key: Py(                                                         0x00007f1ebdda1e30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z_axis",                                                                 Py(                                                                     0x00007f1ebdda1e60,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb652c0,                                                 ),                                                 validator: DefinitionRef(                                                     DefinitionRefValidator {                                                         definition: "...",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "GetSketchModePlane",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee60a840,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "GetSketchModePlane",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1f20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1e00,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66df0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_sketch_mode_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddf0c40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66df0,                                                 ),                                             ],                                         },                                         expected_repr: "'get_sketch_mode_plane'",                                         name: "literal['get_sketch_mode_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_sketch_mode_plane']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetSketchModePlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee22980,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionGetSketchModePlane",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.get_sketch_mode_plane.GetSketchModePlane, type: Literal['get_sketch_mode_plane'] = 'get_sketch_mode_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: GetSketchModePlane

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=GetSketchModePlane, required=True), 'type': FieldInfo(annotation=Literal['get_sketch_mode_plane'], required=False, default='get_sketch_mode_plane')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_sketch_mode_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragEnd(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.handle_mouse_drag_end.HandleMouseDragEnd'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['handle_mouse_drag_end']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 577

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragEnd'>, 'config': {'title': 'OptionHandleMouseDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragEnd'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragEnd:94394502995824', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.handle_mouse_drag_end.HandleMouseDragEnd'>, 'config': {'title': 'HandleMouseDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.handle_mouse_drag_end.HandleMouseDragEnd'>>]}, 'ref': 'kittycad.models.handle_mouse_drag_end.HandleMouseDragEnd:94394495582384', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'HandleMouseDragEnd', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'handle_mouse_drag_end', 'schema': {'expected': ['handle_mouse_drag_end'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragEnd', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragEnd, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_end'], required=False, default='handle_mouse_drag_end')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed1df70,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee60c0b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "HandleMouseDragEnd",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66af0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_end",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_end']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragEnd",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragEnd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99b60,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde99980,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "HandleMouseDragEnd",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee60c0b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "HandleMouseDragEnd",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde997d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde997a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66af0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_end": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd5bcc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66af0,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_end'",                                         name: "literal['handle_mouse_drag_end']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_end']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragEnd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed1df70,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionHandleMouseDragEnd",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.handle_mouse_drag_end.HandleMouseDragEnd, type: Literal['handle_mouse_drag_end'] = 'handle_mouse_drag_end') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: HandleMouseDragEnd

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragEnd, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_end'], required=False, default='handle_mouse_drag_end')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['handle_mouse_drag_end']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragMove(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.handle_mouse_drag_move.HandleMouseDragMove'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['handle_mouse_drag_move']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 567

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragMove'>, 'config': {'title': 'OptionHandleMouseDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragMove'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragMove:94394502986336', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.handle_mouse_drag_move.HandleMouseDragMove'>, 'config': {'title': 'HandleMouseDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.handle_mouse_drag_move.HandleMouseDragMove'>>]}, 'ref': 'kittycad.models.handle_mouse_drag_move.HandleMouseDragMove:94394495596240', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'HandleMouseDragMove', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'handle_mouse_drag_move', 'schema': {'expected': ['handle_mouse_drag_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragMove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragMove, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_move'], required=False, default='handle_mouse_drag_move')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed1ba60,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee669f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_move",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee60f6d0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "HandleMouseDragMove",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragMove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9abe0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9a580,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "HandleMouseDragMove",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee60f6d0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "HandleMouseDragMove",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9a610,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9a820,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee669f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd5ae00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee669f0,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_move'",                                         name: "literal['handle_mouse_drag_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_move']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed1ba60,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionHandleMouseDragMove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.handle_mouse_drag_move.HandleMouseDragMove, type: Literal['handle_mouse_drag_move'] = 'handle_mouse_drag_move') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: HandleMouseDragMove

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragMove, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_move'], required=False, default='handle_mouse_drag_move')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['handle_mouse_drag_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragStart(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.handle_mouse_drag_start.HandleMouseDragStart'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['handle_mouse_drag_start']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 557

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragStart'>, 'config': {'title': 'OptionHandleMouseDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragStart'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionHandleMouseDragStart:94394502977136', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.handle_mouse_drag_start.HandleMouseDragStart'>, 'config': {'title': 'HandleMouseDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.handle_mouse_drag_start.HandleMouseDragStart'>>]}, 'ref': 'kittycad.models.handle_mouse_drag_start.HandleMouseDragStart:94394495606480', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'HandleMouseDragStart', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'handle_mouse_drag_start', 'schema': {'expected': ['handle_mouse_drag_start'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragStart', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragStart, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_start'], required=False, default='handle_mouse_drag_start')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed19670,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee611ed0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "HandleMouseDragStart",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee668f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_start",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_start']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragStart",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragStart", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde999b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9b060,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "HandleMouseDragStart",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee611ed0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "HandleMouseDragStart",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9a7f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9ae80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee668f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_start": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd59e80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee668f0,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_start'",                                         name: "literal['handle_mouse_drag_start']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_start']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragStart",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed19670,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionHandleMouseDragStart",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.handle_mouse_drag_start.HandleMouseDragStart, type: Literal['handle_mouse_drag_start'] = 'handle_mouse_drag_start') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: HandleMouseDragStart

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HandleMouseDragStart, required=True), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_start'], required=False, default='handle_mouse_drag_start')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['handle_mouse_drag_start']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntities(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.highlight_set_entities.HighlightSetEntities'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['highlight_set_entities']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 307

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntities'>, 'config': {'title': 'OptionHighlightSetEntities'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntities'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntities:94394502307504', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.highlight_set_entities.HighlightSetEntities'>, 'config': {'title': 'HighlightSetEntities'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.highlight_set_entities.HighlightSetEntities'>>]}, 'ref': 'kittycad.models.highlight_set_entities.HighlightSetEntities:94394493899680', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'HighlightSetEntities', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'highlight_set_entities', 'schema': {'expected': ['highlight_set_entities'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHighlightSetEntities', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HighlightSetEntities, required=True), 'type': FieldInfo(annotation=Literal['highlight_set_entities'], required=False, default='highlight_set_entities')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec75eb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee667f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "highlight_set_entities",                                             },                                             expected_py: None,                                             name: "literal['highlight_set_entities']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee4713a0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "HighlightSetEntities",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHighlightSetEntities",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHighlightSetEntities", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9b930,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9bdb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "HighlightSetEntities",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee4713a0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "HighlightSetEntities",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b690,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9b9c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee667f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "highlight_set_entities": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd22e00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee667f0,                                                 ),                                             ],                                         },                                         expected_repr: "'highlight_set_entities'",                                         name: "literal['highlight_set_entities']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['highlight_set_entities']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHighlightSetEntities",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec75eb0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionHighlightSetEntities",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.highlight_set_entities.HighlightSetEntities, type: Literal['highlight_set_entities'] = 'highlight_set_entities') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: HighlightSetEntities

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HighlightSetEntities, required=True), 'type': FieldInfo(annotation=Literal['highlight_set_entities'], required=False, default='highlight_set_entities')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['highlight_set_entities']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntity(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.highlight_set_entity.HighlightSetEntity'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['highlight_set_entity']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 729

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntity'>, 'config': {'title': 'OptionHighlightSetEntity'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntity'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionHighlightSetEntity:94394503167568', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.highlight_set_entity.HighlightSetEntity'>, 'config': {'title': 'HighlightSetEntity'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.highlight_set_entity.HighlightSetEntity'>>]}, 'ref': 'kittycad.models.highlight_set_entity.HighlightSetEntity:94394495592624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'sequence': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'HighlightSetEntity', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'highlight_set_entity', 'schema': {'expected': ['highlight_set_entity'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHighlightSetEntity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HighlightSetEntity, required=True), 'type': FieldInfo(annotation=Literal['highlight_set_entity'], required=False, default='highlight_set_entity')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed47e50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee60e8b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe494bb0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "sequence": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f05e10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Int(                                                                             IntSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "HighlightSetEntity",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee666f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "highlight_set_entity",                                             },                                             expected_py: None,                                             name: "literal['highlight_set_entity']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHighlightSetEntity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHighlightSetEntity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34420,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd349c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_id",                                                 lookup_key: Simple {                                                     key: "entity_id",                                                     py_key: Py(                                                         0x00007f1ebdd76570,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_id",                                                                 Py(                                                                     0x00007f1ebdd76530,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe494bb0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "sequence",                                                 lookup_key: Simple {                                                     key: "sequence",                                                     py_key: Py(                                                         0x00007f1ebdd765f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "sequence",                                                                 Py(                                                                     0x00007f1ebdd765b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f05e10,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Int(                                                                     IntValidator {                                                                         strict: false,                                                                     },                                                                 ),                                                                 name: "nullable[int]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[int]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "HighlightSetEntity",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee60e8b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "HighlightSetEntity",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34a50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd342a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee666f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "highlight_set_entity": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd76680,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee666f0,                                                 ),                                             ],                                         },                                         expected_repr: "'highlight_set_entity'",                                         name: "literal['highlight_set_entity']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['highlight_set_entity']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHighlightSetEntity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed47e50,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionHighlightSetEntity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.highlight_set_entity.HighlightSetEntity, type: Literal['highlight_set_entity'] = 'highlight_set_entity') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: HighlightSetEntity

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=HighlightSetEntity, required=True), 'type': FieldInfo(annotation=Literal['highlight_set_entity'], required=False, default='highlight_set_entity')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['highlight_set_entity']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionImportFiles(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.import_files.ImportFiles'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['import_files']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1211

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionImportFiles'>, 'config': {'title': 'OptionImportFiles'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionImportFiles'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionImportFiles:94394503968384', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.import_files.ImportFiles'>, 'config': {'title': 'ImportFiles'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.import_files.ImportFiles'>>]}, 'ref': 'kittycad.models.import_files.ImportFiles:94394495685424', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ImportFiles', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'import_files', 'schema': {'expected': ['import_files'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionImportFiles', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ImportFiles, required=True), 'type': FieldInfo(annotation=Literal['import_files'], required=False, default='import_files')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee0b680,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee625330,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "object_id": SerField {                                                     key_py: Py(                                                         0x00007f1ec0d43c30,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ImportFiles",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee660f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "import_files",                                             },                                             expected_py: None,                                             name: "literal['import_files']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionImportFiles",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionImportFiles", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7d50,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded59e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "object_id",                                                 lookup_key: Simple {                                                     key: "object_id",                                                     py_key: Py(                                                         0x00007f1ebddd67f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "object_id",                                                                 Py(                                                                     0x00007f1ebddd54b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec0d43c30,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ImportFiles",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee625330,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ImportFiles",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6970,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7d20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee660f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "import_files": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddac140,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee660f0,                                                 ),                                             ],                                         },                                         expected_repr: "'import_files'",                                         name: "literal['import_files']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['import_files']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionImportFiles",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee0b680,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionImportFiles",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.import_files.ImportFiles, type: Literal['import_files'] = 'import_files') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ImportFiles

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ImportFiles, required=True), 'type': FieldInfo(annotation=Literal['import_files'], required=False, default='import_files')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['import_files']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionImportedGeometry(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.imported_geometry.ImportedGeometry'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['imported_geometry']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1221

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionImportedGeometry'>, 'config': {'title': 'OptionImportedGeometry'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionImportedGeometry'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionImportedGeometry:94394503979600', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.imported_geometry.ImportedGeometry'>, 'config': {'title': 'ImportedGeometry'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.imported_geometry.ImportedGeometry'>>]}, 'ref': 'kittycad.models.imported_geometry.ImportedGeometry:94394495691824', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'value': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'ImportedGeometry', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'imported_geometry', 'schema': {'expected': ['imported_geometry'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionImportedGeometry', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ImportedGeometry, required=True), 'type': FieldInfo(annotation=Literal['imported_geometry'], required=False, default='imported_geometry')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee0e250,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee626c30,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "id": SerField {                                                     key_py: Py(                                                         0x00007f1ec28215c0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "value": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f06de8,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ImportedGeometry",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee66030,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "imported_geometry",                                             },                                             expected_py: None,                                             name: "literal['imported_geometry']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionImportedGeometry",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionImportedGeometry", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded73c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7690,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "id",                                                 lookup_key: Simple {                                                     key: "id",                                                     py_key: Py(                                                         0x00007f1ebded7000,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "id",                                                                 Py(                                                                     0x00007f1ebded7030,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec28215c0,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "value",                                                 lookup_key: Simple {                                                     key: "value",                                                     py_key: Py(                                                         0x00007f1ebded73f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "value",                                                                 Py(                                                                     0x00007f1ebded7120,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f06de8,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ImportedGeometry",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee626c30,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ImportedGeometry",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7870,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7450,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee66030,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "imported_geometry": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddb9300,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee66030,                                                 ),                                             ],                                         },                                         expected_repr: "'imported_geometry'",                                         name: "literal['imported_geometry']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['imported_geometry']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionImportedGeometry",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee0e250,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionImportedGeometry",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.imported_geometry.ImportedGeometry, type: Literal['imported_geometry'] = 'imported_geometry') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ImportedGeometry

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ImportedGeometry, required=True), 'type': FieldInfo(annotation=Literal['imported_geometry'], required=False, default='imported_geometry')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['imported_geometry']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionLoft(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.loft.Loft'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['loft']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 789

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionLoft'>, 'config': {'title': 'OptionLoft'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionLoft'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionLoft:94394503241856', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.loft.Loft'>, 'config': {'title': 'Loft'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.loft.Loft'>>]}, 'ref': 'kittycad.models.loft.Loft:94394495964176', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'solid_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'Loft', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'loft', 'schema': {'expected': ['loft'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionLoft', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Loft, required=True), 'type': FieldInfo(annotation=Literal['loft'], required=False, default='loft')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed5a080,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee669410,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "solid_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe291230,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Loft",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf269740,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "loft",                                             },                                             expected_py: None,                                             name: "literal['loft']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionLoft",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionLoft", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6e20,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5530,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "solid_id",                                                 lookup_key: Simple {                                                     key: "solid_id",                                                     py_key: Py(                                                         0x00007f1ebdd8c7f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "solid_id",                                                                 Py(                                                                     0x00007f1ebdd8c7b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe291230,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Loft",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee669410,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Loft",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5560,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5500,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf269740,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "loft": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd8c840,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf269740,                                                 ),                                             ],                                         },                                         expected_repr: "'loft'",                                         name: "literal['loft']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['loft']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionLoft",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed5a080,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionLoft",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.loft.Loft, type: Literal['loft'] = 'loft') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Loft

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Loft, required=True), 'type': FieldInfo(annotation=Literal['loft'], required=False, default='loft')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['loft']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMakeAxesGizmo(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.make_axes_gizmo.MakeAxesGizmo'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['make_axes_gizmo']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 547

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMakeAxesGizmo'>, 'config': {'title': 'OptionMakeAxesGizmo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMakeAxesGizmo'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMakeAxesGizmo:94394502967648', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.make_axes_gizmo.MakeAxesGizmo'>, 'config': {'title': 'MakeAxesGizmo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.make_axes_gizmo.MakeAxesGizmo'>>]}, 'ref': 'kittycad.models.make_axes_gizmo.MakeAxesGizmo:94394495971536', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'MakeAxesGizmo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'make_axes_gizmo', 'schema': {'expected': ['make_axes_gizmo'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMakeAxesGizmo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakeAxesGizmo, required=True), 'type': FieldInfo(annotation=Literal['make_axes_gizmo'], required=False, default='make_axes_gizmo')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed17160,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee601b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_axes_gizmo",                                             },                                             expected_py: None,                                             name: "literal['make_axes_gizmo']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee66b0d0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MakeAxesGizmo",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakeAxesGizmo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakeAxesGizmo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9bfc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9bc90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "MakeAxesGizmo",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee66b0d0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MakeAxesGizmo",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9bc00,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9af40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee601b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_axes_gizmo": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd58f80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee601b0,                                                 ),                                             ],                                         },                                         expected_repr: "'make_axes_gizmo'",                                         name: "literal['make_axes_gizmo']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_axes_gizmo']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakeAxesGizmo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed17160,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMakeAxesGizmo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.make_axes_gizmo.MakeAxesGizmo, type: Literal['make_axes_gizmo'] = 'make_axes_gizmo') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MakeAxesGizmo

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakeAxesGizmo, required=True), 'type': FieldInfo(annotation=Literal['make_axes_gizmo'], required=False, default='make_axes_gizmo')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['make_axes_gizmo']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMakeOffsetPath(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.make_offset_path.MakeOffsetPath'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['make_offset_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 909

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMakeOffsetPath'>, 'config': {'title': 'OptionMakeOffsetPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMakeOffsetPath'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMakeOffsetPath:94394503568432', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.make_offset_path.MakeOffsetPath'>, 'config': {'title': 'MakeOffsetPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.make_offset_path.MakeOffsetPath'>>]}, 'ref': 'kittycad.models.make_offset_path.MakeOffsetPath:94394495976944', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'MakeOffsetPath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'make_offset_path', 'schema': {'expected': ['make_offset_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMakeOffsetPath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakeOffsetPath, required=True), 'type': FieldInfo(annotation=Literal['make_offset_path'], required=False, default='make_offset_path')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eeda9c30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee60270,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_offset_path",                                             },                                             expected_py: None,                                             name: "literal['make_offset_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee66c5f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MakeOffsetPath",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakeOffsetPath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakeOffsetPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9b210,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9b8a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebddbdbf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebddbdbb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "MakeOffsetPath",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee66c5f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MakeOffsetPath",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9bb70,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9af10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee60270,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_offset_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbdc40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee60270,                                                 ),                                             ],                                         },                                         expected_repr: "'make_offset_path'",                                         name: "literal['make_offset_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_offset_path']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakeOffsetPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eeda9c30,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMakeOffsetPath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.make_offset_path.MakeOffsetPath, type: Literal['make_offset_path'] = 'make_offset_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MakeOffsetPath

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakeOffsetPath, required=True), 'type': FieldInfo(annotation=Literal['make_offset_path'], required=False, default='make_offset_path')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['make_offset_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMakePlane(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.make_plane.MakePlane'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['make_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 427

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMakePlane'>, 'config': {'title': 'OptionMakePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMakePlane'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMakePlane:94394502133760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.make_plane.MakePlane'>, 'config': {'title': 'MakePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.make_plane.MakePlane'>>]}, 'ref': 'kittycad.models.make_plane.MakePlane:94394495982352', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'MakePlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'make_plane', 'schema': {'expected': ['make_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMakePlane', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakePlane, required=True), 'type': FieldInfo(annotation=Literal['make_plane'], required=False, default='make_plane')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec4b800,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee602f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_plane",                                             },                                             expected_py: None,                                             name: "literal['make_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee66db10,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MakePlane",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakePlane",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakePlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5bf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5c20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "MakePlane",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee66db10,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MakePlane",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5c50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5c80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee602f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd03a00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee602f0,                                                 ),                                             ],                                         },                                         expected_repr: "'make_plane'",                                         name: "literal['make_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_plane']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakePlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec4b800,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMakePlane",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.make_plane.MakePlane, type: Literal['make_plane'] = 'make_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MakePlane

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MakePlane, required=True), 'type': FieldInfo(annotation=Literal['make_plane'], required=False, default='make_plane')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['make_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMass(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.mass.Mass'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['mass']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1231

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMass'>, 'config': {'title': 'OptionMass'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMass'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMass:94394503992464', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.mass.Mass'>, 'config': {'title': 'Mass'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.mass.Mass'>>]}, 'ref': 'kittycad.models.mass.Mass:94394495987760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'mass': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'output_unit': {'metadata': {}, 'schema': {'cls': <enum 'UnitMass'>, 'members': [UnitMass.G, UnitMass.KG, UnitMass.LB], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_mass.UnitMass:94394491882240', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'Mass', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'mass', 'schema': {'expected': ['mass'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMass', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Mass, required=True), 'type': FieldInfo(annotation=Literal['mass'], required=False, default='mass')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee11490,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf269aa0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mass",                                             },                                             expected_py: None,                                             name: "literal['mass']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9ee66f030,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "mass": SerField {                                                     key_py: Py(                                                         0x00007f1ebf269aa0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "output_unit": SerField {                                                     key_py: Py(                                                         0x00007f1ebebb86b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee284b00,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Mass",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMass",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMass", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3030,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2f10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "mass",                                                 lookup_key: Simple {                                                     key: "mass",                                                     py_key: Py(                                                         0x00007f1ebdda3000,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "mass",                                                                 Py(                                                                     0x00007f1ebdda2f40,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf269aa0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "output_unit",                                                 lookup_key: Simple {                                                     key: "output_unit",                                                     py_key: Py(                                                         0x00007f1ebdde5fb0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "output_unit",                                                                 Py(                                                                     0x00007f1ebdde5f70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebebb86b0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee284b00,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "g": 0,                                                                     "kg": 1,                                                                     "lb": 2,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdde5f00,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe5f1a90,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1af0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1b50,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'g', 'kg' or 'lb'",                                                         strict: false,                                                         class_repr: "UnitMass",                                                         name: "str-enum[UnitMass]",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Mass",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9ee66f030,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Mass",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2c10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda2c40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf269aa0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mass": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde6000,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf269aa0,                                                 ),                                             ],                                         },                                         expected_repr: "'mass'",                                         name: "literal['mass']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mass']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMass",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee11490,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMass",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.mass.Mass, type: Literal['mass'] = 'mass') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Mass

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Mass, required=True), 'type': FieldInfo(annotation=Literal['mass'], required=False, default='mass')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['mass']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMouseClick(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.mouse_click.MouseClick'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['mouse_click']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1069

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMouseClick'>, 'config': {'title': 'OptionMouseClick'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMouseClick'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMouseClick:94394503736448', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.mouse_click.MouseClick'>, 'config': {'title': 'MouseClick'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.mouse_click.MouseClick'>>]}, 'ref': 'kittycad.models.mouse_click.MouseClick:94394502083376', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entities_modified': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'entities_selected': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'MouseClick', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'mouse_click', 'schema': {'expected': ['mouse_click'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMouseClick', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MouseClick, required=True), 'type': FieldInfo(annotation=Literal['mouse_click'], required=False, default='mouse_click')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedd2c80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec3f330,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entities_selected": SerField {                                                     key_py: Py(                                                         0x00007f1ebe1e5ef0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "entities_modified": SerField {                                                     key_py: Py(                                                         0x00007f1ebe1e5230,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MouseClick",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee60d30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mouse_click",                                             },                                             expected_py: None,                                             name: "literal['mouse_click']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMouseClick",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMouseClick", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9b600,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9bab0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entities_modified",                                                 lookup_key: Simple {                                                     key: "entities_modified",                                                     py_key: Py(                                                         0x00007f1ebdf221f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entities_modified",                                                                 Py(                                                                     0x00007f1ebdf21ff0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe1e5230,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "entities_selected",                                                 lookup_key: Simple {                                                     key: "entities_selected",                                                     py_key: Py(                                                         0x00007f1ebdf21970,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entities_selected",                                                                 Py(                                                                     0x00007f1ebdf21530,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe1e5ef0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "MouseClick",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec3f330,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MouseClick",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde99e90,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9bed0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee60d30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mouse_click": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf21740,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee60d30,                                                 ),                                             ],                                         },                                         expected_repr: "'mouse_click'",                                         name: "literal['mouse_click']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mouse_click']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMouseClick",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedd2c80,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMouseClick",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.mouse_click.MouseClick, type: Literal['mouse_click'] = 'mouse_click') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MouseClick

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MouseClick, required=True), 'type': FieldInfo(annotation=Literal['mouse_click'], required=False, default='mouse_click')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['mouse_click']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMouseMove(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.mouse_move.MouseMove'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['mouse_move']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 457

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMouseMove'>, 'config': {'title': 'OptionMouseMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMouseMove'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMouseMove:94394502883200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.mouse_move.MouseMove'>, 'config': {'title': 'MouseMove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.mouse_move.MouseMove'>>]}, 'ref': 'kittycad.models.mouse_move.MouseMove:94394502092752', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'MouseMove', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'mouse_move', 'schema': {'expected': ['mouse_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMouseMove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MouseMove, required=True), 'type': FieldInfo(annotation=Literal['mouse_move'], required=False, default='mouse_move')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed02780,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee60db0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mouse_move",                                             },                                             expected_py: None,                                             name: "literal['mouse_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec417d0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MouseMove",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMouseMove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMouseMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded66a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded66d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "MouseMove",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec417d0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MouseMove",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6700,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6730,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee60db0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mouse_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd4a600,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee60db0,                                                 ),                                             ],                                         },                                         expected_repr: "'mouse_move'",                                         name: "literal['mouse_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mouse_move']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMouseMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed02780,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMouseMove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.mouse_move.MouseMove, type: Literal['mouse_move'] = 'mouse_move') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MouseMove

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MouseMove, required=True), 'type': FieldInfo(annotation=Literal['mouse_move'], required=False, default='mouse_move')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['mouse_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionMovePathPen(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.move_path_pen.MovePathPen'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['move_path_pen']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 165

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionMovePathPen'>, 'config': {'title': 'OptionMovePathPen'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionMovePathPen'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionMovePathPen:94394500590544', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.move_path_pen.MovePathPen'>, 'config': {'title': 'MovePathPen'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.move_path_pen.MovePathPen'>>]}, 'ref': 'kittycad.models.move_path_pen.MovePathPen:94394502082288', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'MovePathPen', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'move_path_pen', 'schema': {'expected': ['move_path_pen'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMovePathPen', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MovePathPen, required=True), 'type': FieldInfo(annotation=Literal['move_path_pen'], required=False, default='move_path_pen')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eead2bd0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec3eef0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "MovePathPen",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee60e30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "move_path_pen",                                             },                                             expected_py: None,                                             name: "literal['move_path_pen']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMovePathPen",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMovePathPen", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34f00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd34ed0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "MovePathPen",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec3eef0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "MovePathPen",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34ea0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34f60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee60e30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "move_path_pen": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd21900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee60e30,                                                 ),                                             ],                                         },                                         expected_repr: "'move_path_pen'",                                         name: "literal['move_path_pen']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['move_path_pen']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMovePathPen",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eead2bd0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionMovePathPen",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.move_path_pen.MovePathPen, type: Literal['move_path_pen'] = 'move_path_pen') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: MovePathPen

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=MovePathPen, required=True), 'type': FieldInfo(annotation=Literal['move_path_pen'], required=False, default='move_path_pen')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['move_path_pen']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionNewAnnotation(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.new_annotation.NewAnnotation'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['new_annotation']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 317

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionNewAnnotation'>, 'config': {'title': 'OptionNewAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionNewAnnotation'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionNewAnnotation:94394502317168', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.new_annotation.NewAnnotation'>, 'config': {'title': 'NewAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.new_annotation.NewAnnotation'>>]}, 'ref': 'kittycad.models.new_annotation.NewAnnotation:94394502111360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'NewAnnotation', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'new_annotation', 'schema': {'expected': ['new_annotation'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionNewAnnotation', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=NewAnnotation, required=True), 'type': FieldInfo(annotation=Literal['new_annotation'], required=False, default='new_annotation')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec78470,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec46080,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "NewAnnotation",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee60eb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "new_annotation",                                             },                                             expected_py: None,                                             name: "literal['new_annotation']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionNewAnnotation",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionNewAnnotation", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9bd80,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36b50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "NewAnnotation",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec46080,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "NewAnnotation",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd367c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd37090,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee60eb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "new_annotation": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebe071f00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee60eb0,                                                 ),                                             ],                                         },                                         expected_repr: "'new_annotation'",                                         name: "literal['new_annotation']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['new_annotation']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionNewAnnotation",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec78470,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionNewAnnotation",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.new_annotation.NewAnnotation, type: Literal['new_annotation'] = 'new_annotation') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: NewAnnotation

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=NewAnnotation, required=True), 'type': FieldInfo(annotation=Literal['new_annotation'], required=False, default='new_annotation')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['new_annotation']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionObjectBringToFront(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.object_bring_to_front.ObjectBringToFront'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['object_bring_to_front']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 357

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectBringToFront'>, 'config': {'title': 'OptionObjectBringToFront'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectBringToFront'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionObjectBringToFront:94394502354384', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.object_bring_to_front.ObjectBringToFront'>, 'config': {'title': 'ObjectBringToFront'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.object_bring_to_front.ObjectBringToFront'>>]}, 'ref': 'kittycad.models.object_bring_to_front.ObjectBringToFront:94394502126304', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'ObjectBringToFront', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'object_bring_to_front', 'schema': {'expected': ['object_bring_to_front'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectBringToFront', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectBringToFront, required=True), 'type': FieldInfo(annotation=Literal['object_bring_to_front'], required=False, default='object_bring_to_front')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec815d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61130,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_bring_to_front",                                             },                                             expected_py: None,                                             name: "literal['object_bring_to_front']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec49ae0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ObjectBringToFront",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectBringToFront",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectBringToFront", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35830,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd341b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "ObjectBringToFront",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec49ae0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ObjectBringToFront",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34150,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd359b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61130,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_bring_to_front": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd0ab80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61130,                                                 ),                                             ],                                         },                                         expected_repr: "'object_bring_to_front'",                                         name: "literal['object_bring_to_front']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_bring_to_front']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectBringToFront",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec815d0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionObjectBringToFront",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.object_bring_to_front.ObjectBringToFront, type: Literal['object_bring_to_front'] = 'object_bring_to_front') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ObjectBringToFront

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectBringToFront, required=True), 'type': FieldInfo(annotation=Literal['object_bring_to_front'], required=False, default='object_bring_to_front')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_bring_to_front']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionObjectSetMaterialParamsPbr(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.object_set_material_params_pbr.ObjectSetMaterialParamsPbr'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['object_set_material_params_pbr']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 367

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectSetMaterialParamsPbr'>, 'config': {'title': 'OptionObjectSetMaterialParamsPbr'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectSetMaterialParamsPbr'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionObjectSetMaterialParamsPbr:94394502363376', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.object_set_material_params_pbr.ObjectSetMaterialParamsPbr'>, 'config': {'title': 'ObjectSetMaterialParamsPbr'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.object_set_material_params_pbr.ObjectSetMaterialParamsPbr'>>]}, 'ref': 'kittycad.models.object_set_material_params_pbr.ObjectSetMaterialParamsPbr:94394502104144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'ObjectSetMaterialParamsPbr', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'object_set_material_params_pbr', 'schema': {'expected': ['object_set_material_params_pbr'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectSetMaterialParamsPbr', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectSetMaterialParamsPbr, required=True), 'type': FieldInfo(annotation=Literal['object_set_material_params_pbr'], required=False, default='object_set_material_params_pbr')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec838f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec44450,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ObjectSetMaterialParamsPbr",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78030,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_set_material_params_pbr",                                             },                                             expected_py: None,                                             name: "literal['object_set_material_params_pbr']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectSetMaterialParamsPbr",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectSetMaterialParamsPbr", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd36190,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd361f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "ObjectSetMaterialParamsPbr",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec44450,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ObjectSetMaterialParamsPbr",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36130,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36160,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78030,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_set_material_params_pbr": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd09d00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78030,                                                 ),                                             ],                                         },                                         expected_repr: "'object_set_material_params_pbr'",                                         name: "literal['object_set_material_params_pbr']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_set_material_params_pbr']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectSetMaterialParamsPbr",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec838f0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionObjectSetMaterialParamsPbr",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.object_set_material_params_pbr.ObjectSetMaterialParamsPbr, type: Literal['object_set_material_params_pbr'] = 'object_set_material_params_pbr') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ObjectSetMaterialParamsPbr

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectSetMaterialParamsPbr, required=True), 'type': FieldInfo(annotation=Literal['object_set_material_params_pbr'], required=False, default='object_set_material_params_pbr')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_set_material_params_pbr']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionObjectVisible(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.object_visible.ObjectVisible'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['object_visible']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 347

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectVisible'>, 'config': {'title': 'OptionObjectVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionObjectVisible'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionObjectVisible:94394502344928', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.object_visible.ObjectVisible'>, 'config': {'title': 'ObjectVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.object_visible.ObjectVisible'>>]}, 'ref': 'kittycad.models.object_visible.ObjectVisible:94394502132768', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'ObjectVisible', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'object_visible', 'schema': {'expected': ['object_visible'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectVisible', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectVisible, required=True), 'type': FieldInfo(annotation=Literal['object_visible'], required=False, default='object_visible')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec7f0e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61270,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_visible",                                             },                                             expected_py: None,                                             name: "literal['object_visible']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec4b420,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ObjectVisible",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectVisible",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectVisible", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34900,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd345a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "ObjectVisible",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec4b420,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ObjectVisible",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd346c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34780,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61270,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_visible": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd0ba80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61270,                                                 ),                                             ],                                         },                                         expected_repr: "'object_visible'",                                         name: "literal['object_visible']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_visible']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectVisible",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec7f0e0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionObjectVisible",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.object_visible.ObjectVisible, type: Literal['object_visible'] = 'object_visible') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ObjectVisible

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ObjectVisible, required=True), 'type': FieldInfo(annotation=Literal['object_visible'], required=False, default='object_visible')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_visible']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionOrientToFace(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.orient_to_face.OrientToFace'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['orient_to_face']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 879

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionOrientToFace'>, 'config': {'title': 'OptionOrientToFace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionOrientToFace'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionOrientToFace:94394503483792', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.orient_to_face.OrientToFace'>, 'config': {'title': 'OrientToFace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.orient_to_face.OrientToFace'>>]}, 'ref': 'kittycad.models.orient_to_face.OrientToFace:94394502662080', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OrientToFace', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'orient_to_face', 'schema': {'expected': ['orient_to_face'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionOrientToFace', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=OrientToFace, required=True), 'type': FieldInfo(annotation=Literal['orient_to_face'], required=False, default='orient_to_face')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed95190,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eeccc7c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "OrientToFace",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee617f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "orient_to_face",                                             },                                             expected_py: None,                                             name: "literal['orient_to_face']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionOrientToFace",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionOrientToFace", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35080,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36250,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebddb8f30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebddb8f70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebdd36c40,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebdd36370,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebdd37360,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebdd36a30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebddb8e70,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebddb8e30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebdd36bb0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebdd36610,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebddb8ef0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebddb8eb0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebdd36b80,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebdd36460,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebdd36550,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebdd37000,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "OrientToFace",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eeccc7c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "OrientToFace",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36580,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd35f20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee617f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "orient_to_face": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddb8fc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee617f0,                                                 ),                                             ],                                         },                                         expected_repr: "'orient_to_face'",                                         name: "literal['orient_to_face']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['orient_to_face']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionOrientToFace",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed95190,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionOrientToFace",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.orient_to_face.OrientToFace, type: Literal['orient_to_face'] = 'orient_to_face') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: OrientToFace

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=OrientToFace, required=True), 'type': FieldInfo(annotation=Literal['orient_to_face'], required=False, default='orient_to_face')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['orient_to_face']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuid(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_get_curve_uuid.PathGetCurveUuid'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_get_curve_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1121

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuid'>, 'config': {'title': 'OptionPathGetCurveUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuid'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuid:94394503813952', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_get_curve_uuid.PathGetCurveUuid'>, 'config': {'title': 'PathGetCurveUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_get_curve_uuid.PathGetCurveUuid'>>]}, 'ref': 'kittycad.models.path_get_curve_uuid.PathGetCurveUuid:94394502779696', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_id': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'PathGetCurveUuid', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_get_curve_uuid', 'schema': {'expected': ['path_get_curve_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetCurveUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetCurveUuid, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuid'], required=False, default='path_get_curve_uuid')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eede5b40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eece9330,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "curve_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe437bf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathGetCurveUuid",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61bf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_curve_uuid",                                             },                                             expected_py: None,                                             name: "literal['path_get_curve_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetCurveUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetCurveUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0060,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0120,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "curve_id",                                                 lookup_key: Simple {                                                     key: "curve_id",                                                     py_key: Py(                                                         0x00007f1ebdf33cf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "curve_id",                                                                 Py(                                                                     0x00007f1ebdf33c70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe437bf0,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathGetCurveUuid",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eece9330,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathGetCurveUuid",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0030,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda01b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61bf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_curve_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf33b80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61bf0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_curve_uuid'",                                         name: "literal['path_get_curve_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_curve_uuid']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetCurveUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eede5b40,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathGetCurveUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_get_curve_uuid.PathGetCurveUuid, type: Literal['path_get_curve_uuid'] = 'path_get_curve_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathGetCurveUuid

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetCurveUuid, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuid'], required=False, default='path_get_curve_uuid')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_curve_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuidsForVertices(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_get_curve_uuids_for_vertices.PathGetCurveUuidsForVertices'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_get_curve_uuids_for_vertices']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1109

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuidsForVertices'>, 'config': {'title': 'OptionPathGetCurveUuidsForVertices'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuidsForVertices'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathGetCurveUuidsForVertices:94394503801664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_get_curve_uuids_for_vertices.PathGetCurveUuidsForVertices'>, 'config': {'title': 'PathGetCurveUuidsForVertices'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_get_curve_uuids_for_vertices.PathGetCurveUuidsForVertices'>>]}, 'ref': 'kittycad.models.path_get_curve_uuids_for_vertices.PathGetCurveUuidsForVertices:94394502604352', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'PathGetCurveUuidsForVertices', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_get_curve_uuids_for_vertices', 'schema': {'expected': ['path_get_curve_uuids_for_vertices'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetCurveUuidsForVertices', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetCurveUuidsForVertices, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuids_for_vertices'], required=False, default='path_get_curve_uuids_for_vertices')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eede2b40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78300,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_curve_uuids_for_vertices",                                             },                                             expected_py: None,                                             name: "literal['path_get_curve_uuids_for_vertices']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecbe640,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "curve_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebdd327b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathGetCurveUuidsForVertices",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetCurveUuidsForVertices",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetCurveUuidsForVertices", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0f00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0d50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "curve_ids",                                                 lookup_key: Simple {                                                     key: "curve_ids",                                                     py_key: Py(                                                         0x00007f1ebdf32730,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "curve_ids",                                                                 Py(                                                                     0x00007f1ebdf32a70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebdd327b0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathGetCurveUuidsForVertices",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecbe640,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathGetCurveUuidsForVertices",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0d80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0d20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78300,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_curve_uuids_for_vertices": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf324c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78300,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_curve_uuids_for_vertices'",                                         name: "literal['path_get_curve_uuids_for_vertices']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_curve_uuids_for_vertices']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetCurveUuidsForVertices",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eede2b40,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathGetCurveUuidsForVertices",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_get_curve_uuids_for_vertices.PathGetCurveUuidsForVertices, type: Literal['path_get_curve_uuids_for_vertices'] = 'path_get_curve_uuids_for_vertices') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathGetCurveUuidsForVertices

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetCurveUuidsForVertices, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuids_for_vertices'], required=False, default='path_get_curve_uuids_for_vertices')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_curve_uuids_for_vertices']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathGetInfo(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_get_info.PathGetInfo'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_get_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1089

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetInfo'>, 'config': {'title': 'OptionPathGetInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetInfo'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathGetInfo:94394503765216', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_get_info.PathGetInfo'>, 'config': {'title': 'PathGetInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_get_info.PathGetInfo'>>]}, 'ref': 'kittycad.models.path_get_info.PathGetInfo:94394502088784', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'segments': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.path_segment_info.PathSegmentInfo'>, 'config': {'title': 'PathSegmentInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment_info.PathSegmentInfo'>>]}, 'ref': 'kittycad.models.path_segment_info.PathSegmentInfo:94394502093744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'command': {'metadata': {}, 'schema': {'cls': <enum 'PathCommand'>, 'members': [PathCommand.MOVE_TO, PathCommand.LINE_TO, PathCommand.BEZ_CURVE_TO, PathCommand.NURBS_CURVE_TO, PathCommand.ADD_ARC], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.path_command.PathCommand:94394502611744', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'command_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}}, 'model_name': 'PathSegmentInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'PathGetInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_get_info', 'schema': {'expected': ['path_get_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetInfo, required=True), 'type': FieldInfo(annotation=Literal['path_get_info'], required=False, default='path_get_info')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedd9ce0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61cf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_info",                                             },                                             expected_py: None,                                             name: "literal['path_get_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec40850,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "segments": SerField {                                                     key_py: Py(                                                         0x00007f1ec1a676f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9eec41bb0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "command_id": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ebdf236b0,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             WithDefault(                                                                                                 WithDefaultSerializer {                                                                                                     default: Default(                                                                                                         Py(                                                                                                             0x00007f1ec2ed0400,                                                                                                         ),                                                                                                     ),                                                                                                     serializer: Nullable(                                                                                                         NullableSerializer {                                                                                                             serializer: Str(                                                                                                                 StrSerializer,                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "command": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f01c40,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Enum(                                                                                                 EnumSerializer {                                                                                                     class: Py(                                                                                                         0x000055d9eecc0320,                                                                                                     ),                                                                                                     serializer: Some(                                                                                                         Str(                                                                                                             StrSerializer,                                                                                                         ),                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "relative": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec157be30,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Bool(                                                                                                 BoolSerializer,                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 3,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "PathSegmentInfo",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[PathSegmentInfo]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathGetInfo",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda18c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1a10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "segments",                                                 lookup_key: Simple {                                                     key: "segments",                                                     py_key: Py(                                                         0x00007f1ebe0730f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "segments",                                                                 Py(                                                                     0x00007f1ebe0734f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1a676f0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "command",                                                                                     lookup_key: Simple {                                                                                         key: "command",                                                                                         py_key: Py(                                                                                             0x00007f1ebdda1a40,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "command",                                                                                                     Py(                                                                                                         0x00007f1ebdda1ad0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f01c40,                                                                                     ),                                                                                     validator: StrEnum(                                                                                         EnumValidator {                                                                                             phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                             class: Py(                                                                                                 0x000055d9eecc0320,                                                                                             ),                                                                                             lookup: LiteralLookup {                                                                                                 expected_bool: None,                                                                                                 expected_int: None,                                                                                                 expected_str: Some(                                                                                                     {                                                                                                         "bez_curve_to": 2,                                                                                                         "nurbs_curve_to": 3,                                                                                                         "add_arc": 4,                                                                                                         "move_to": 0,                                                                                                         "line_to": 1,                                                                                                     },                                                                                                 ),                                                                                                 expected_py_dict: None,                                                                                                 expected_py_values: None,                                                                                                 expected_py_primitives: Some(                                                                                                     Py(                                                                                                         0x00007f1ebdf70740,                                                                                                     ),                                                                                                 ),                                                                                                 values: [                                                                                                     Py(                                                                                                         0x00007f1ebdea8770,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebdea8830,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebdea87d0,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebdea8890,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebdea88f0,                                                                                                     ),                                                                                                 ],                                                                                             },                                                                                             missing: None,                                                                                             expected_repr: "'move_to', 'line_to', 'bez_curve_to', 'nurbs_curve_to' or 'add_arc'",                                                                                             strict: false,                                                                                             class_repr: "PathCommand",                                                                                             name: "str-enum[PathCommand]",                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "command_id",                                                                                     lookup_key: Simple {                                                                                         key: "command_id",                                                                                         py_key: Py(                                                                                             0x00007f1ebdf18db0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "command_id",                                                                                                     Py(                                                                                                         0x00007f1ebdf1b830,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ebdf236b0,                                                                                     ),                                                                                     validator: WithDefault(                                                                                         WithDefaultValidator {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             on_error: Raise,                                                                                             validator: Nullable(                                                                                                 NullableValidator {                                                                                                     validator: FunctionAfter(                                                                                                         FunctionAfterValidator {                                                                                                             validator: Str(                                                                                                                 StrValidator {                                                                                                                     strict: false,                                                                                                                     coerce_numbers_to_str: false,                                                                                                                 },                                                                                                             ),                                                                                                             func: Py(                                                                                                                 0x000055d9ee75c500,                                                                                                             ),                                                                                                             config: Py(                                                                                                                 0x00007f1ebdf717c0,                                                                                                             ),                                                                                                             name: "function-after[ModelingCmdId(), str]",                                                                                                             field_name: None,                                                                                                             info_arg: false,                                                                                                         },                                                                                                     ),                                                                                                     name: "nullable[function-after[ModelingCmdId(), str]]",                                                                                                 },                                                                                             ),                                                                                             validate_default: false,                                                                                             copy_default: false,                                                                                             name: "default[nullable[function-after[ModelingCmdId(), str]]]",                                                                                             undefined: Py(                                                                                                 0x00007f1ec0cae3d0,                                                                                             ),                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "relative",                                                                                     lookup_key: Simple {                                                                                         key: "relative",                                                                                         py_key: Py(                                                                                             0x00007f1ebe0de7f0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "relative",                                                                                                     Py(                                                                                                         0x00007f1ebe0730b0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec157be30,                                                                                     ),                                                                                     validator: Bool(                                                                                         BoolValidator {                                                                                             strict: false,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "PathSegmentInfo",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9eec41bb0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "PathSegmentInfo",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathGetInfo",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec40850,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathGetInfo",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1b00,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1b60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61cf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebe0569c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61cf0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_info'",                                         name: "literal['path_get_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_info']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedd9ce0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathGetInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_get_info.PathGetInfo, type: Literal['path_get_info'] = 'path_get_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathGetInfo

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetInfo, required=True), 'type': FieldInfo(annotation=Literal['path_get_info'], required=False, default='path_get_info')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathGetSketchTargetUuid(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_get_sketch_target_uuid.PathGetSketchTargetUuid'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_get_sketch_target_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1141

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetSketchTargetUuid'>, 'config': {'title': 'OptionPathGetSketchTargetUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetSketchTargetUuid'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathGetSketchTargetUuid:94394503837456', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_get_sketch_target_uuid.PathGetSketchTargetUuid'>, 'config': {'title': 'PathGetSketchTargetUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_get_sketch_target_uuid.PathGetSketchTargetUuid'>>]}, 'ref': 'kittycad.models.path_get_sketch_target_uuid.PathGetSketchTargetUuid:94394502656432', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'target_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'PathGetSketchTargetUuid', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_get_sketch_target_uuid', 'schema': {'expected': ['path_get_sketch_target_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetSketchTargetUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetSketchTargetUuid, required=True), 'type': FieldInfo(annotation=Literal['path_get_sketch_target_uuid'], required=False, default='path_get_sketch_target_uuid')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedeb710,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eeccb1b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "target_id": SerField {                                                     key_py: Py(                                                         0x00007f1ec28cc230,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathGetSketchTargetUuid",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee783a0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_sketch_target_uuid",                                             },                                             expected_py: None,                                             name: "literal['path_get_sketch_target_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetSketchTargetUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetSketchTargetUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda24f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2520,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "target_id",                                                 lookup_key: Simple {                                                     key: "target_id",                                                     py_key: Py(                                                         0x00007f1ebdde0230,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "target_id",                                                                 Py(                                                                     0x00007f1ebdde01f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec28cc230,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathGetSketchTargetUuid",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eeccb1b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathGetSketchTargetUuid",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2550,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda2580,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee783a0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_sketch_target_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde0280,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee783a0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_sketch_target_uuid'",                                         name: "literal['path_get_sketch_target_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_sketch_target_uuid']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetSketchTargetUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedeb710,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathGetSketchTargetUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_get_sketch_target_uuid.PathGetSketchTargetUuid, type: Literal['path_get_sketch_target_uuid'] = 'path_get_sketch_target_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathGetSketchTargetUuid

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetSketchTargetUuid, required=True), 'type': FieldInfo(annotation=Literal['path_get_sketch_target_uuid'], required=False, default='path_get_sketch_target_uuid')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_sketch_target_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathGetVertexUuids(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_get_vertex_uuids.PathGetVertexUuids'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_get_vertex_uuids']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1131

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetVertexUuids'>, 'config': {'title': 'OptionPathGetVertexUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathGetVertexUuids'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathGetVertexUuids:94394503825216', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_get_vertex_uuids.PathGetVertexUuids'>, 'config': {'title': 'PathGetVertexUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_get_vertex_uuids.PathGetVertexUuids'>>]}, 'ref': 'kittycad.models.path_get_vertex_uuids.PathGetVertexUuids:94394502802208', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'vertex_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'PathGetVertexUuids', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_get_vertex_uuids', 'schema': {'expected': ['path_get_vertex_uuids'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetVertexUuids', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetVertexUuids, required=True), 'type': FieldInfo(annotation=Literal['path_get_vertex_uuids'], required=False, default='path_get_vertex_uuids')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eede8740,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eeceeb20,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "vertex_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebe13ffb0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathGetVertexUuids",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61e70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_vertex_uuids",                                             },                                             expected_py: None,                                             name: "literal['path_get_vertex_uuids']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetVertexUuids",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetVertexUuids", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0780,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda07b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "vertex_ids",                                                 lookup_key: Simple {                                                     key: "vertex_ids",                                                     py_key: Py(                                                         0x00007f1ebddd4b30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "vertex_ids",                                                                 Py(                                                                     0x00007f1ebddd4a70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe13ffb0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathGetVertexUuids",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eeceeb20,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathGetVertexUuids",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda20a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda21f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61e70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_vertex_uuids": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddd4bc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61e70,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_vertex_uuids'",                                         name: "literal['path_get_vertex_uuids']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_vertex_uuids']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetVertexUuids",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eede8740,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathGetVertexUuids",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_get_vertex_uuids.PathGetVertexUuids, type: Literal['path_get_vertex_uuids'] = 'path_get_vertex_uuids') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathGetVertexUuids

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathGetVertexUuids, required=True), 'type': FieldInfo(annotation=Literal['path_get_vertex_uuids'], required=False, default='path_get_vertex_uuids')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_vertex_uuids']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPathSegmentInfo(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.path_segment_info.PathSegmentInfo'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['path_segment_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1099

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPathSegmentInfo'>, 'config': {'title': 'OptionPathSegmentInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPathSegmentInfo'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPathSegmentInfo:94394503785344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.path_segment_info.PathSegmentInfo'>, 'config': {'title': 'PathSegmentInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment_info.PathSegmentInfo'>>]}, 'ref': 'kittycad.models.path_segment_info.PathSegmentInfo:94394502093744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'command': {'metadata': {}, 'schema': {'cls': <enum 'PathCommand'>, 'members': [PathCommand.MOVE_TO, PathCommand.LINE_TO, PathCommand.BEZ_CURVE_TO, PathCommand.NURBS_CURVE_TO, PathCommand.ADD_ARC], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.path_command.PathCommand:94394502611744', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'command_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}}, 'model_name': 'PathSegmentInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'path_segment_info', 'schema': {'expected': ['path_segment_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathSegmentInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathSegmentInfo, required=True), 'type': FieldInfo(annotation=Literal['path_segment_info'], required=False, default='path_segment_info')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eeddeb80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec41bb0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "command_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebdf236b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "relative": SerField {                                                     key_py: Py(                                                         0x00007f1ec157be30,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Bool(                                                             BoolSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "command": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f01c40,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9eecc0320,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 3,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PathSegmentInfo",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee61ff0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_segment_info",                                             },                                             expected_py: None,                                             name: "literal['path_segment_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathSegmentInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathSegmentInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda12c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1290,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "command",                                                 lookup_key: Simple {                                                     key: "command",                                                     py_key: Py(                                                         0x00007f1ebdda1410,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "command",                                                                 Py(                                                                     0x00007f1ebdda1380,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f01c40,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9eecc0320,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "nurbs_curve_to": 3,                                                                     "line_to": 1,                                                                     "move_to": 0,                                                                     "add_arc": 4,                                                                     "bez_curve_to": 2,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdf68b40,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebdea8770,                                                                 ),                                                                 Py(                                                                     0x00007f1ebdea8830,                                                                 ),                                                                 Py(                                                                     0x00007f1ebdea87d0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebdea8890,                                                                 ),                                                                 Py(                                                                     0x00007f1ebdea88f0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'move_to', 'line_to', 'bez_curve_to', 'nurbs_curve_to' or 'add_arc'",                                                         strict: false,                                                         class_repr: "PathCommand",                                                         name: "str-enum[PathCommand]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "command_id",                                                 lookup_key: Simple {                                                     key: "command_id",                                                     py_key: Py(                                                         0x00007f1ebdf6bbf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "command_id",                                                                 Py(                                                                     0x00007f1ebdf6a970,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebdf236b0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: FunctionAfter(                                                                     FunctionAfterValidator {                                                                         validator: Str(                                                                             StrValidator {                                                                                 strict: false,                                                                                 coerce_numbers_to_str: false,                                                                             },                                                                         ),                                                                         func: Py(                                                                             0x000055d9ee75c500,                                                                         ),                                                                         config: Py(                                                                             0x00007f1ebdf68980,                                                                         ),                                                                         name: "function-after[ModelingCmdId(), str]",                                                                         field_name: None,                                                                         info_arg: false,                                                                     },                                                                 ),                                                                 name: "nullable[function-after[ModelingCmdId(), str]]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[function-after[ModelingCmdId(), str]]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "relative",                                                 lookup_key: Simple {                                                     key: "relative",                                                     py_key: Py(                                                         0x00007f1ebdf6b8f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "relative",                                                                 Py(                                                                     0x00007f1ebdf6b6f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec157be30,                                                 ),                                                 validator: Bool(                                                     BoolValidator {                                                         strict: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PathSegmentInfo",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec41bb0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PathSegmentInfo",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1320,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1110,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee61ff0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_segment_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf6b200,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee61ff0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_segment_info'",                                         name: "literal['path_segment_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_segment_info']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathSegmentInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eeddeb80,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPathSegmentInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.path_segment_info.PathSegmentInfo, type: Literal['path_segment_info'] = 'path_segment_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PathSegmentInfo

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PathSegmentInfo, required=True), 'type': FieldInfo(annotation=Literal['path_segment_info'], required=False, default='path_segment_info')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_segment_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPlaneIntersectAndProject(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.plane_intersect_and_project.PlaneIntersectAndProject'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['plane_intersect_and_project']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1201

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPlaneIntersectAndProject'>, 'config': {'title': 'OptionPlaneIntersectAndProject'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPlaneIntersectAndProject'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPlaneIntersectAndProject:94394503949760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.plane_intersect_and_project.PlaneIntersectAndProject'>, 'config': {'title': 'PlaneIntersectAndProject'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.plane_intersect_and_project.PlaneIntersectAndProject'>>]}, 'ref': 'kittycad.models.plane_intersect_and_project.PlaneIntersectAndProject:94394502652512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'plane_coordinates': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94394496976608', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'PlaneIntersectAndProject', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'plane_intersect_and_project', 'schema': {'expected': ['plane_intersect_and_project'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPlaneIntersectAndProject', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PlaneIntersectAndProject, required=True), 'type': FieldInfo(annotation=Literal['plane_intersect_and_project'], required=False, default='plane_intersect_and_project')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee06dc0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecca260,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "plane_coordinates": SerField {                                                     key_py: Py(                                                         0x00007f1ebdd2f8f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055d9ee7606e0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "y": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "x": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 2,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Point2d",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PlaneIntersectAndProject",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee784e0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "plane_intersect_and_project",                                             },                                             expected_py: None,                                             name: "literal['plane_intersect_and_project']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPlaneIntersectAndProject",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPlaneIntersectAndProject", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34ba0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35b90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "plane_coordinates",                                                 lookup_key: Simple {                                                     key: "plane_coordinates",                                                     py_key: Py(                                                         0x00007f1ebdf215b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "plane_coordinates",                                                                 Py(                                                                     0x00007f1ebdf211f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebdd2f8f0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "x",                                                                                         lookup_key: Simple {                                                                                             key: "x",                                                                                             py_key: Py(                                                                                                 0x00007f1ec2f08838,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "x",                                                                                                         Py(                                                                                                             0x00007f1ec2f08838,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         validator: FunctionAfter(                                                                                             FunctionAfterValidator {                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 func: Py(                                                                                                     0x000055d9ee53edc0,                                                                                                 ),                                                                                                 config: Py(                                                                                                     0x00007f1ebdf23340,                                                                                                 ),                                                                                                 name: "function-after[LengthUnit(), float]",                                                                                                 field_name: None,                                                                                                 info_arg: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "y",                                                                                         lookup_key: Simple {                                                                                             key: "y",                                                                                             py_key: Py(                                                                                                 0x00007f1ec2f08868,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "y",                                                                                                         Py(                                                                                                             0x00007f1ec2f08868,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         validator: FunctionAfter(                                                                                             FunctionAfterValidator {                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 func: Py(                                                                                                     0x000055d9ee53edc0,                                                                                                 ),                                                                                                 config: Py(                                                                                                     0x00007f1ebdf23340,                                                                                                 ),                                                                                                 name: "function-after[LengthUnit(), float]",                                                                                                 field_name: None,                                                                                                 info_arg: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "Point2d",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055d9ee7606e0,                                                                         ),                                                                         generic_origin: None,                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007f1ec0cae3d0,                                                                         ),                                                                         name: "Point2d",                                                                     },                                                                 ),                                                                 name: "nullable[Point2d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point2d]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "PlaneIntersectAndProject",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecca260,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PlaneIntersectAndProject",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35620,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd37120,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee784e0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "plane_intersect_and_project": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf212c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee784e0,                                                 ),                                             ],                                         },                                         expected_repr: "'plane_intersect_and_project'",                                         name: "literal['plane_intersect_and_project']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['plane_intersect_and_project']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPlaneIntersectAndProject",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee06dc0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPlaneIntersectAndProject",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.plane_intersect_and_project.PlaneIntersectAndProject, type: Literal['plane_intersect_and_project'] = 'plane_intersect_and_project') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PlaneIntersectAndProject

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PlaneIntersectAndProject, required=True), 'type': FieldInfo(annotation=Literal['plane_intersect_and_project'], required=False, default='plane_intersect_and_project')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['plane_intersect_and_project']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionPlaneSetColor(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.plane_set_color.PlaneSetColor'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['plane_set_color']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 437

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionPlaneSetColor'>, 'config': {'title': 'OptionPlaneSetColor'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionPlaneSetColor'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionPlaneSetColor:94394502433024', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.plane_set_color.PlaneSetColor'>, 'config': {'title': 'PlaneSetColor'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.plane_set_color.PlaneSetColor'>>]}, 'ref': 'kittycad.models.plane_set_color.PlaneSetColor:94394502820656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'PlaneSetColor', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'plane_set_color', 'schema': {'expected': ['plane_set_color'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPlaneSetColor', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PlaneSetColor, required=True), 'type': FieldInfo(annotation=Literal['plane_set_color'], required=False, default='plane_set_color')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec94900,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecf3330,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "PlaneSetColor",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee624b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "plane_set_color",                                             },                                             expected_py: None,                                             name: "literal['plane_set_color']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPlaneSetColor",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPlaneSetColor", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5f80,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5fb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "PlaneSetColor",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecf3330,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "PlaneSetColor",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5fe0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6010,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee624b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "plane_set_color": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd48900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee624b0,                                                 ),                                             ],                                         },                                         expected_repr: "'plane_set_color'",                                         name: "literal['plane_set_color']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['plane_set_color']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPlaneSetColor",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec94900,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionPlaneSetColor",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.plane_set_color.PlaneSetColor, type: Literal['plane_set_color'] = 'plane_set_color') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: PlaneSetColor

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=PlaneSetColor, required=True), 'type': FieldInfo(annotation=Literal['plane_set_color'], required=False, default='plane_set_color')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['plane_set_color']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionProjectEntityToPlane(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.project_entity_to_plane.ProjectEntityToPlane'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['project_entity_to_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1039

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionProjectEntityToPlane'>, 'config': {'title': 'OptionProjectEntityToPlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionProjectEntityToPlane'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionProjectEntityToPlane:94394503690784', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.project_entity_to_plane.ProjectEntityToPlane'>, 'config': {'title': 'ProjectEntityToPlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.project_entity_to_plane.ProjectEntityToPlane'>>]}, 'ref': 'kittycad.models.project_entity_to_plane.ProjectEntityToPlane:94394502819664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'projected_points': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'ProjectEntityToPlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'project_entity_to_plane', 'schema': {'expected': ['project_entity_to_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionProjectEntityToPlane', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ProjectEntityToPlane, required=True), 'type': FieldInfo(annotation=Literal['project_entity_to_plane'], required=False, default='project_entity_to_plane')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedc7a20,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee62770,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "project_entity_to_plane",                                             },                                             expected_py: None,                                             name: "literal['project_entity_to_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecf2f50,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "projected_points": SerField {                                                     key_py: Py(                                                         0x00007f1ebdebfbf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9edd655a0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "x": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "y": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "z": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 3,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "Point3d",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[Point3d]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ProjectEntityToPlane",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionProjectEntityToPlane",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionProjectEntityToPlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd36e50,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd364f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "projected_points",                                                 lookup_key: Simple {                                                     key: "projected_points",                                                     py_key: Py(                                                         0x00007f1ebdd819f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "projected_points",                                                                 Py(                                                                     0x00007f1ebdd830b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebdebfbf0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "x",                                                                                     lookup_key: Simple {                                                                                         key: "x",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "x",                                                                                                     Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08838,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "y",                                                                                     lookup_key: Simple {                                                                                         key: "y",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "y",                                                                                                     Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08868,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "z",                                                                                     lookup_key: Simple {                                                                                         key: "z",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "z",                                                                                                     Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08898,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "Point3d",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9edd655a0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "Point3d",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ProjectEntityToPlane",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecf2f50,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ProjectEntityToPlane",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35a70,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36100,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee62770,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "project_entity_to_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd820c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee62770,                                                 ),                                             ],                                         },                                         expected_repr: "'project_entity_to_plane'",                                         name: "literal['project_entity_to_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['project_entity_to_plane']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionProjectEntityToPlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedc7a20,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionProjectEntityToPlane",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.project_entity_to_plane.ProjectEntityToPlane, type: Literal['project_entity_to_plane'] = 'project_entity_to_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ProjectEntityToPlane

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ProjectEntityToPlane, required=True), 'type': FieldInfo(annotation=Literal['project_entity_to_plane'], required=False, default='project_entity_to_plane')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['project_entity_to_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionProjectPointsToPlane(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.project_points_to_plane.ProjectPointsToPlane'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['project_points_to_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1049

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionProjectPointsToPlane'>, 'config': {'title': 'OptionProjectPointsToPlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionProjectPointsToPlane'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionProjectPointsToPlane:94394503707664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.project_points_to_plane.ProjectPointsToPlane'>, 'config': {'title': 'ProjectPointsToPlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.project_points_to_plane.ProjectPointsToPlane'>>]}, 'ref': 'kittycad.models.project_points_to_plane.ProjectPointsToPlane:94394502872624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'projected_points': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'ProjectPointsToPlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'project_points_to_plane', 'schema': {'expected': ['project_points_to_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionProjectPointsToPlane', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ProjectPointsToPlane, required=True), 'type': FieldInfo(annotation=Literal['project_points_to_plane'], required=False, default='project_points_to_plane')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedcbc10,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee62870,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "project_points_to_plane",                                             },                                             expected_py: None,                                             name: "literal['project_points_to_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecffe30,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "projected_points": SerField {                                                     key_py: Py(                                                         0x00007f1ebdebfbf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9edd655a0,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "x": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "z": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "y": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Float(                                                                                                 FloatSerializer {                                                                                                     inf_nan_mode: Null,                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 3,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "Point3d",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[Point3d]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ProjectPointsToPlane",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionProjectPointsToPlane",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionProjectPointsToPlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdf6d740,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdf6d770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "projected_points",                                                 lookup_key: Simple {                                                     key: "projected_points",                                                     py_key: Py(                                                         0x00007f1ebdd008b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "projected_points",                                                                 Py(                                                                     0x00007f1ebdd00cb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebdebfbf0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "x",                                                                                     lookup_key: Simple {                                                                                         key: "x",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08838,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "x",                                                                                                     Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08838,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "y",                                                                                     lookup_key: Simple {                                                                                         key: "y",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08868,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "y",                                                                                                     Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08868,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "z",                                                                                     lookup_key: Simple {                                                                                         key: "z",                                                                                         py_key: Py(                                                                                             0x00007f1ec2f08898,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "z",                                                                                                     Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec2f08898,                                                                                     ),                                                                                     validator: Float(                                                                                         FloatValidator {                                                                                             strict: false,                                                                                             allow_inf_nan: true,                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "Point3d",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9edd655a0,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "Point3d",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ProjectPointsToPlane",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecffe30,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ProjectPointsToPlane",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdf6d800,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdf6d7a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee62870,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "project_points_to_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd97bc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee62870,                                                 ),                                             ],                                         },                                         expected_repr: "'project_points_to_plane'",                                         name: "literal['project_points_to_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['project_points_to_plane']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionProjectPointsToPlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedcbc10,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionProjectPointsToPlane",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.project_points_to_plane.ProjectPointsToPlane, type: Literal['project_points_to_plane'] = 'project_points_to_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ProjectPointsToPlane

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ProjectPointsToPlane, required=True), 'type': FieldInfo(annotation=Literal['project_points_to_plane'], required=False, default='project_points_to_plane')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['project_points_to_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionReconfigureStream(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.reconfigure_stream.ReconfigureStream'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['reconfigure_stream']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 597

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionReconfigureStream'>, 'config': {'title': 'OptionReconfigureStream'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionReconfigureStream'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionReconfigureStream:94394503015072', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.reconfigure_stream.ReconfigureStream'>, 'config': {'title': 'ReconfigureStream'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.reconfigure_stream.ReconfigureStream'>>]}, 'ref': 'kittycad.models.reconfigure_stream.ReconfigureStream:94394502847104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'ReconfigureStream', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'reconfigure_stream', 'schema': {'expected': ['reconfigure_stream'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionReconfigureStream', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ReconfigureStream, required=True), 'type': FieldInfo(annotation=Literal['reconfigure_stream'], required=False, default='reconfigure_stream')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed22aa0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecf9a80,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ReconfigureStream",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee62970,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "reconfigure_stream",                                             },                                             expected_py: None,                                             name: "literal['reconfigure_stream']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionReconfigureStream",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionReconfigureStream", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded65e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded65b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "ReconfigureStream",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecf9a80,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ReconfigureStream",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6550,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6580,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee62970,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "reconfigure_stream": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd61ac0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee62970,                                                 ),                                             ],                                         },                                         expected_repr: "'reconfigure_stream'",                                         name: "literal['reconfigure_stream']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['reconfigure_stream']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionReconfigureStream",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed22aa0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionReconfigureStream",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.reconfigure_stream.ReconfigureStream, type: Literal['reconfigure_stream'] = 'reconfigure_stream') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ReconfigureStream

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ReconfigureStream, required=True), 'type': FieldInfo(annotation=Literal['reconfigure_stream'], required=False, default='reconfigure_stream')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['reconfigure_stream']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionRemoveSceneObjects(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.remove_scene_objects.RemoveSceneObjects'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['remove_scene_objects']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 587

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionRemoveSceneObjects'>, 'config': {'title': 'OptionRemoveSceneObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionRemoveSceneObjects'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionRemoveSceneObjects:94394503005616', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.remove_scene_objects.RemoveSceneObjects'>, 'config': {'title': 'RemoveSceneObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.remove_scene_objects.RemoveSceneObjects'>>]}, 'ref': 'kittycad.models.remove_scene_objects.RemoveSceneObjects:94394502851616', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'RemoveSceneObjects', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'remove_scene_objects', 'schema': {'expected': ['remove_scene_objects'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRemoveSceneObjects', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=RemoveSceneObjects, required=True), 'type': FieldInfo(annotation=Literal['remove_scene_objects'], required=False, default='remove_scene_objects')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed205b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecfac20,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "RemoveSceneObjects",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee62a70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "remove_scene_objects",                                             },                                             expected_py: None,                                             name: "literal['remove_scene_objects']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionRemoveSceneObjects",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRemoveSceneObjects", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6c10,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6ac0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "RemoveSceneObjects",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecfac20,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "RemoveSceneObjects",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6be0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6b20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee62a70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "remove_scene_objects": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd60c00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee62a70,                                                 ),                                             ],                                         },                                         expected_repr: "'remove_scene_objects'",                                         name: "literal['remove_scene_objects']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['remove_scene_objects']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRemoveSceneObjects",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed205b0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionRemoveSceneObjects",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.remove_scene_objects.RemoveSceneObjects, type: Literal['remove_scene_objects'] = 'remove_scene_objects') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: RemoveSceneObjects

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=RemoveSceneObjects, required=True), 'type': FieldInfo(annotation=Literal['remove_scene_objects'], required=False, default='remove_scene_objects')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['remove_scene_objects']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionRevolve(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.revolve.Revolve'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['revolve']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 205

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionRevolve'>, 'config': {'title': 'OptionRevolve'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionRevolve'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionRevolve:94394502567728', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.revolve.Revolve'>, 'config': {'title': 'Revolve'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.revolve.Revolve'>>]}, 'ref': 'kittycad.models.revolve.Revolve:94394502845424', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Revolve', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'revolve', 'schema': {'expected': ['revolve'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRevolve', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Revolve, required=True), 'type': FieldInfo(annotation=Literal['revolve'], required=False, default='revolve')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecb5730,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf26de90,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "revolve",                                             },                                             expected_py: None,                                             name: "literal['revolve']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecf93f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Revolve",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionRevolve",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRevolve", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9b510,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9b9f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Revolve",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecf93f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Revolve",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b270,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9b2a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf26de90,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "revolve": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1e040,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf26de90,                                                 ),                                             ],                                         },                                         expected_repr: "'revolve'",                                         name: "literal['revolve']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['revolve']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRevolve",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecb5730,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionRevolve",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.revolve.Revolve, type: Literal['revolve'] = 'revolve') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Revolve

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Revolve, required=True), 'type': FieldInfo(annotation=Literal['revolve'], required=False, default='revolve')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['revolve']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionRevolveAboutEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.revolve_about_edge.RevolveAboutEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['revolve_about_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 225

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionRevolveAboutEdge'>, 'config': {'title': 'OptionRevolveAboutEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionRevolveAboutEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionRevolveAboutEdge:94394502586192', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.revolve_about_edge.RevolveAboutEdge'>, 'config': {'title': 'RevolveAboutEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.revolve_about_edge.RevolveAboutEdge'>>]}, 'ref': 'kittycad.models.revolve_about_edge.RevolveAboutEdge:94394502862736', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'RevolveAboutEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'revolve_about_edge', 'schema': {'expected': ['revolve_about_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRevolveAboutEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=RevolveAboutEdge, required=True), 'type': FieldInfo(annotation=Literal['revolve_about_edge'], required=False, default='revolve_about_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecb9f50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee62b70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "revolve_about_edge",                                             },                                             expected_py: None,                                             name: "literal['revolve_about_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecfd790,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "RevolveAboutEdge",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionRevolveAboutEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRevolveAboutEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a790,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9a6d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "RevolveAboutEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecfd790,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "RevolveAboutEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9a760,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9b180,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee62b70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "revolve_about_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1c440,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee62b70,                                                 ),                                             ],                                         },                                         expected_repr: "'revolve_about_edge'",                                         name: "literal['revolve_about_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['revolve_about_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRevolveAboutEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecb9f50,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionRevolveAboutEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.revolve_about_edge.RevolveAboutEdge, type: Literal['revolve_about_edge'] = 'revolve_about_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: RevolveAboutEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=RevolveAboutEdge, required=True), 'type': FieldInfo(annotation=Literal['revolve_about_edge'], required=False, default='revolve_about_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['revolve_about_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSceneClearAll(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.scene_clear_all.SceneClearAll'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['scene_clear_all']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 287

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSceneClearAll'>, 'config': {'title': 'OptionSceneClearAll'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSceneClearAll'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSceneClearAll:94394502289104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.scene_clear_all.SceneClearAll'>, 'config': {'title': 'SceneClearAll'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.scene_clear_all.SceneClearAll'>>]}, 'ref': 'kittycad.models.scene_clear_all.SceneClearAll:94394502843792', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SceneClearAll', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'scene_clear_all', 'schema': {'expected': ['scene_clear_all'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSceneClearAll', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SceneClearAll, required=True), 'type': FieldInfo(annotation=Literal['scene_clear_all'], required=False, default='scene_clear_all')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec716d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecf8d90,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SceneClearAll",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63070,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "scene_clear_all",                                             },                                             expected_py: None,                                             name: "literal['scene_clear_all']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSceneClearAll",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSceneClearAll", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99740,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9a670,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SceneClearAll",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecf8d90,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SceneClearAll",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9a730,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9a280,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63070,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "scene_clear_all": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebde93f40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63070,                                                 ),                                             ],                                         },                                         expected_repr: "'scene_clear_all'",                                         name: "literal['scene_clear_all']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['scene_clear_all']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSceneClearAll",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec716d0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSceneClearAll",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.scene_clear_all.SceneClearAll, type: Literal['scene_clear_all'] = 'scene_clear_all') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SceneClearAll

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SceneClearAll, required=True), 'type': FieldInfo(annotation=Literal['scene_clear_all'], required=False, default='scene_clear_all')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['scene_clear_all']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectAdd(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_add.SelectAdd'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_add']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 267

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectAdd'>, 'config': {'title': 'OptionSelectAdd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectAdd'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectAdd:94394502270576', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_add.SelectAdd'>, 'config': {'title': 'SelectAdd'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_add.SelectAdd'>>]}, 'ref': 'kittycad.models.select_add.SelectAdd:94394502157600', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SelectAdd', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_add', 'schema': {'expected': ['select_add'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectAdd', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectAdd, required=True), 'type': FieldInfo(annotation=Literal['select_add'], required=False, default='select_add')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec6ce70,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec51520,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectAdd",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63270,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_add",                                             },                                             expected_py: None,                                             name: "literal['select_add']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectAdd",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectAdd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded55c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded55f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SelectAdd",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec51520,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectAdd",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5620,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5650,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63270,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_add": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd10b00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63270,                                                 ),                                             ],                                         },                                         expected_repr: "'select_add'",                                         name: "literal['select_add']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_add']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectAdd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec6ce70,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectAdd",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_add.SelectAdd, type: Literal['select_add'] = 'select_add') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectAdd

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectAdd, required=True), 'type': FieldInfo(annotation=Literal['select_add'], required=False, default='select_add')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_add']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectClear(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_clear.SelectClear'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_clear']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 679

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectClear'>, 'config': {'title': 'OptionSelectClear'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectClear'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectClear:94394503090320', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_clear.SelectClear'>, 'config': {'title': 'SelectClear'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_clear.SelectClear'>>]}, 'ref': 'kittycad.models.select_clear.SelectClear:94394502860640', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SelectClear', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_clear', 'schema': {'expected': ['select_clear'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectClear', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectClear, required=True), 'type': FieldInfo(annotation=Literal['select_clear'], required=False, default='select_clear')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed35090,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee632f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_clear",                                             },                                             expected_py: None,                                             name: "literal['select_clear']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecfcf60,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectClear",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectClear",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectClear", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7c30,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7c60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SelectClear",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecfcf60,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectClear",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded7c90,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7cc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee632f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_clear": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd75340,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee632f0,                                                 ),                                             ],                                         },                                         expected_repr: "'select_clear'",                                         name: "literal['select_clear']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_clear']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectClear",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed35090,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectClear",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_clear.SelectClear, type: Literal['select_clear'] = 'select_clear') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectClear

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectClear, required=True), 'type': FieldInfo(annotation=Literal['select_clear'], required=False, default='select_clear')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_clear']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectGet(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_get.SelectGet'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_get']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 949

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectGet'>, 'config': {'title': 'OptionSelectGet'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectGet'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectGet:94394503611328', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_get.SelectGet'>, 'config': {'title': 'SelectGet'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_get.SelectGet'>>]}, 'ref': 'kittycad.models.select_get.SelectGet:94394502164000', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'SelectGet', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_get', 'schema': {'expected': ['select_get'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectGet', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectGet, required=True), 'type': FieldInfo(annotation=Literal['select_get'], required=False, default='select_get')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedb43c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63370,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_get",                                             },                                             expected_py: None,                                             name: "literal['select_get']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec52e20,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_ids": SerField {                                                     key_py: Py(                                                         0x00007f1ebf0f9ab0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectGet",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectGet",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectGet", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0de0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0e10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_ids",                                                 lookup_key: Simple {                                                     key: "entity_ids",                                                     py_key: Py(                                                         0x00007f1ebddc9d30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_ids",                                                                 Py(                                                                     0x00007f1ebddc9cf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebf0f9ab0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "SelectGet",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec52e20,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectGet",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0e40,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0e70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63370,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_get": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddc9d80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63370,                                                 ),                                             ],                                         },                                         expected_repr: "'select_get'",                                         name: "literal['select_get']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_get']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectGet",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedb43c0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectGet",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_get.SelectGet, type: Literal['select_get'] = 'select_get') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectGet

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectGet, required=True), 'type': FieldInfo(annotation=Literal['select_get'], required=False, default='select_get')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_get']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectRemove(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_remove.SelectRemove'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_remove']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 277

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectRemove'>, 'config': {'title': 'OptionSelectRemove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectRemove'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectRemove:94394502280320', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_remove.SelectRemove'>, 'config': {'title': 'SelectRemove'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_remove.SelectRemove'>>]}, 'ref': 'kittycad.models.select_remove.SelectRemove:94394502171392', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SelectRemove', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_remove', 'schema': {'expected': ['select_remove'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectRemove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectRemove, required=True), 'type': FieldInfo(annotation=Literal['select_remove'], required=False, default='select_remove')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec6f480,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec54b00,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectRemove",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee633f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_remove",                                             },                                             expected_py: None,                                             name: "literal['select_remove']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectRemove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectRemove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99c80,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9acd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SelectRemove",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec54b00,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectRemove",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde99e60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde99f20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee633f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_remove": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebde0dfc0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee633f0,                                                 ),                                             ],                                         },                                         expected_repr: "'select_remove'",                                         name: "literal['select_remove']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_remove']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectRemove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec6f480,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectRemove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_remove.SelectRemove, type: Literal['select_remove'] = 'select_remove') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectRemove

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectRemove, required=True), 'type': FieldInfo(annotation=Literal['select_remove'], required=False, default='select_remove')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_remove']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectReplace(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_replace.SelectReplace'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_replace']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 297

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectReplace'>, 'config': {'title': 'OptionSelectReplace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectReplace'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectReplace:94394502298560', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_replace.SelectReplace'>, 'config': {'title': 'SelectReplace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_replace.SelectReplace'>>]}, 'ref': 'kittycad.models.select_replace.SelectReplace:94394502176800', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SelectReplace', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_replace', 'schema': {'expected': ['select_replace'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectReplace', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectReplace, required=True), 'type': FieldInfo(annotation=Literal['select_replace'], required=False, default='select_replace')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec73bc0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec56020,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectReplace",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63470,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_replace",                                             },                                             expected_py: None,                                             name: "literal['select_replace']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectReplace",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectReplace", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9afa0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9aee0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SelectReplace",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec56020,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectReplace",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b000,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9af70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63470,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_replace": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebeddae00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63470,                                                 ),                                             ],                                         },                                         expected_repr: "'select_replace'",                                         name: "literal['select_replace']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_replace']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectReplace",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec73bc0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectReplace",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_replace.SelectReplace, type: Literal['select_replace'] = 'select_replace') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectReplace

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectReplace, required=True), 'type': FieldInfo(annotation=Literal['select_replace'], required=False, default='select_replace')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_replace']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSelectWithPoint(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.select_with_point.SelectWithPoint'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['select_with_point']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 719

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectWithPoint'>, 'config': {'title': 'OptionSelectWithPoint'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSelectWithPoint'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSelectWithPoint:94394503155360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.select_with_point.SelectWithPoint'>, 'config': {'title': 'SelectWithPoint'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_with_point.SelectWithPoint'>>]}, 'ref': 'kittycad.models.select_with_point.SelectWithPoint:94394502175744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'SelectWithPoint', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'select_with_point', 'schema': {'expected': ['select_with_point'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectWithPoint', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectWithPoint, required=True), 'type': FieldInfo(annotation=Literal['select_with_point'], required=False, default='select_with_point')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed44ea0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63530,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_with_point",                                             },                                             expected_py: None,                                             name: "literal['select_with_point']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec55c00,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "entity_id": SerField {                                                     key_py: Py(                                                         0x00007f1ebe494bb0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SelectWithPoint",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectWithPoint",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectWithPoint", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35350,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35110,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "entity_id",                                                 lookup_key: Simple {                                                     key: "entity_id",                                                     py_key: Py(                                                         0x00007f1ebdd13a70,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "entity_id",                                                                 Py(                                                                     0x00007f1ebdd101b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe494bb0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "SelectWithPoint",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec55c00,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SelectWithPoint",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd352c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd351d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63530,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_with_point": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd23e00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63530,                                                 ),                                             ],                                         },                                         expected_repr: "'select_with_point'",                                         name: "literal['select_with_point']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_with_point']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectWithPoint",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed44ea0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSelectWithPoint",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.select_with_point.SelectWithPoint, type: Literal['select_with_point'] = 'select_with_point') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SelectWithPoint

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SelectWithPoint, required=True), 'type': FieldInfo(annotation=Literal['select_with_point'], required=False, default='select_with_point')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_with_point']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSendObject(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.send_object.SendObject'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['send_object']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 397

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSendObject'>, 'config': {'title': 'OptionSendObject'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSendObject'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSendObject:94394502392544', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.send_object.SendObject'>, 'config': {'title': 'SendObject'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.send_object.SendObject'>>]}, 'ref': 'kittycad.models.send_object.SendObject:94394502188016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SendObject', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'send_object', 'schema': {'expected': ['send_object'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSendObject', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SendObject, required=True), 'type': FieldInfo(annotation=Literal['send_object'], required=False, default='send_object')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec8aae0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec58bf0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SendObject",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63630,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "send_object",                                             },                                             expected_py: None,                                             name: "literal['send_object']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSendObject",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSendObject", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd37270,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd370f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SendObject",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec58bf0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SendObject",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd37150,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd37210,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63630,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "send_object": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd00f00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63630,                                                 ),                                             ],                                         },                                         expected_repr: "'send_object'",                                         name: "literal['send_object']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['send_object']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSendObject",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec8aae0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSendObject",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.send_object.SendObject, type: Literal['send_object'] = 'send_object') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SendObject

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SendObject, required=True), 'type': FieldInfo(annotation=Literal['send_object'], required=False, default='send_object')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['send_object']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetBackgroundColor(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_background_color.SetBackgroundColor'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_background_color']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 517

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetBackgroundColor'>, 'config': {'title': 'OptionSetBackgroundColor'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetBackgroundColor'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetBackgroundColor:94394502938928', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_background_color.SetBackgroundColor'>, 'config': {'title': 'SetBackgroundColor'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_background_color.SetBackgroundColor'>>]}, 'ref': 'kittycad.models.set_background_color.SetBackgroundColor:94394502870320', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetBackgroundColor', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_background_color', 'schema': {'expected': ['set_background_color'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetBackgroundColor', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetBackgroundColor, required=True), 'type': FieldInfo(annotation=Literal['set_background_color'], required=False, default='set_background_color')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed10130,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63970,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_background_color",                                             },                                             expected_py: None,                                             name: "literal['set_background_color']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecff530,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetBackgroundColor",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetBackgroundColor",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetBackgroundColor", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34720,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd343f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetBackgroundColor",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecff530,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetBackgroundColor",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34870,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd359e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63970,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_background_color": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd0b600,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63970,                                                 ),                                             ],                                         },                                         expected_repr: "'set_background_color'",                                         name: "literal['set_background_color']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_background_color']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetBackgroundColor",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed10130,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetBackgroundColor",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_background_color.SetBackgroundColor, type: Literal['set_background_color'] = 'set_background_color') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetBackgroundColor

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetBackgroundColor, required=True), 'type': FieldInfo(annotation=Literal['set_background_color'], required=False, default='set_background_color')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_background_color']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetCurrentToolProperties(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_current_tool_properties.SetCurrentToolProperties'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_current_tool_properties']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 527

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetCurrentToolProperties'>, 'config': {'title': 'OptionSetCurrentToolProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetCurrentToolProperties'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetCurrentToolProperties:94394502948096', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_current_tool_properties.SetCurrentToolProperties'>, 'config': {'title': 'SetCurrentToolProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_current_tool_properties.SetCurrentToolProperties'>>]}, 'ref': 'kittycad.models.set_current_tool_properties.SetCurrentToolProperties:94394502193296', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetCurrentToolProperties', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_current_tool_properties', 'schema': {'expected': ['set_current_tool_properties'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetCurrentToolProperties', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetCurrentToolProperties, required=True), 'type': FieldInfo(annotation=Literal['set_current_tool_properties'], required=False, default='set_current_tool_properties')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed12500,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee786c0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_current_tool_properties",                                             },                                             expected_py: None,                                             name: "literal['set_current_tool_properties']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec5a090,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetCurrentToolProperties",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetCurrentToolProperties",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetCurrentToolProperties", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34db0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd350b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetCurrentToolProperties",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec5a090,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetCurrentToolProperties",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34d20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd353b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee786c0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_current_tool_properties": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd0b380,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee786c0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_current_tool_properties'",                                         name: "literal['set_current_tool_properties']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_current_tool_properties']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetCurrentToolProperties",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed12500,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetCurrentToolProperties",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_current_tool_properties.SetCurrentToolProperties, type: Literal['set_current_tool_properties'] = 'set_current_tool_properties') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetCurrentToolProperties

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetCurrentToolProperties, required=True), 'type': FieldInfo(annotation=Literal['set_current_tool_properties'], required=False, default='set_current_tool_properties')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_current_tool_properties']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetDefaultSystemProperties(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_default_system_properties.SetDefaultSystemProperties'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_default_system_properties']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 537

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetDefaultSystemProperties'>, 'config': {'title': 'OptionSetDefaultSystemProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetDefaultSystemProperties'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetDefaultSystemProperties:94394502957904', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_default_system_properties.SetDefaultSystemProperties'>, 'config': {'title': 'SetDefaultSystemProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_default_system_properties.SetDefaultSystemProperties'>>]}, 'ref': 'kittycad.models.set_default_system_properties.SetDefaultSystemProperties:94394502200416', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetDefaultSystemProperties', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_default_system_properties', 'schema': {'expected': ['set_default_system_properties'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetDefaultSystemProperties', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetDefaultSystemProperties, required=True), 'type': FieldInfo(annotation=Literal['set_default_system_properties'], required=False, default='set_default_system_properties')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed14b50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec5bc60,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetDefaultSystemProperties",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78760,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_default_system_properties",                                             },                                             expected_py: None,                                             name: "literal['set_default_system_properties']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetDefaultSystemProperties",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetDefaultSystemProperties", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34600,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd34c60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetDefaultSystemProperties",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec5bc60,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetDefaultSystemProperties",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35ef0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd35530,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78760,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_default_system_properties": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd12f00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78760,                                                 ),                                             ],                                         },                                         expected_repr: "'set_default_system_properties'",                                         name: "literal['set_default_system_properties']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_default_system_properties']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetDefaultSystemProperties",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed14b50,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetDefaultSystemProperties",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_default_system_properties.SetDefaultSystemProperties, type: Literal['set_default_system_properties'] = 'set_default_system_properties') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetDefaultSystemProperties

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetDefaultSystemProperties, required=True), 'type': FieldInfo(annotation=Literal['set_default_system_properties'], required=False, default='set_default_system_properties')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_default_system_properties']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetGridReferencePlane(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_grid_reference_plane.SetGridReferencePlane'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_grid_reference_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1411

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetGridReferencePlane'>, 'config': {'title': 'OptionSetGridReferencePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetGridReferencePlane'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetGridReferencePlane:94394504236256', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_grid_reference_plane.SetGridReferencePlane'>, 'config': {'title': 'SetGridReferencePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_grid_reference_plane.SetGridReferencePlane'>>]}, 'ref': 'kittycad.models.set_grid_reference_plane.SetGridReferencePlane:94394502198976', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetGridReferencePlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_grid_reference_plane', 'schema': {'expected': ['set_grid_reference_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetGridReferencePlane', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetGridReferencePlane, required=True), 'type': FieldInfo(annotation=Literal['set_grid_reference_plane'], required=False, default='set_grid_reference_plane')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee4cce0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78800,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_grid_reference_plane",                                             },                                             expected_py: None,                                             name: "literal['set_grid_reference_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec5b6c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetGridReferencePlane",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetGridReferencePlane",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetGridReferencePlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda3090,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2c70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetGridReferencePlane",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec5b6c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetGridReferencePlane",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda30c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1860,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78800,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_grid_reference_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdc14900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78800,                                                 ),                                             ],                                         },                                         expected_repr: "'set_grid_reference_plane'",                                         name: "literal['set_grid_reference_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_grid_reference_plane']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetGridReferencePlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee4cce0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetGridReferencePlane",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_grid_reference_plane.SetGridReferencePlane, type: Literal['set_grid_reference_plane'] = 'set_grid_reference_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetGridReferencePlane

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetGridReferencePlane, required=True), 'type': FieldInfo(annotation=Literal['set_grid_reference_plane'], required=False, default='set_grid_reference_plane')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_grid_reference_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetObjectTransform(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_object_transform.SetObjectTransform'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_object_transform']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 919

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetObjectTransform'>, 'config': {'title': 'OptionSetObjectTransform'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetObjectTransform'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetObjectTransform:94394503580464', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_object_transform.SetObjectTransform'>, 'config': {'title': 'SetObjectTransform'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_object_transform.SetObjectTransform'>>]}, 'ref': 'kittycad.models.set_object_transform.SetObjectTransform:94394502205104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetObjectTransform', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_object_transform', 'schema': {'expected': ['set_object_transform'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetObjectTransform', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetObjectTransform, required=True), 'type': FieldInfo(annotation=Literal['set_object_transform'], required=False, default='set_object_transform')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedacb30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63c30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_object_transform",                                             },                                             expected_py: None,                                             name: "literal['set_object_transform']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec5ceb0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetObjectTransform",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetObjectTransform",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetObjectTransform", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde99fe0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde99770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetObjectTransform",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec5ceb0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetObjectTransform",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde996b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde99800,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63c30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_object_transform": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbeb00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63c30,                                                 ),                                             ],                                         },                                         expected_repr: "'set_object_transform'",                                         name: "literal['set_object_transform']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_object_transform']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetObjectTransform",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedacb30,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetObjectTransform",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_object_transform.SetObjectTransform, type: Literal['set_object_transform'] = 'set_object_transform') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetObjectTransform

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetObjectTransform, required=True), 'type': FieldInfo(annotation=Literal['set_object_transform'], required=False, default='set_object_transform')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_object_transform']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetSceneUnits(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_scene_units.SetSceneUnits'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_scene_units']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 607

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSceneUnits'>, 'config': {'title': 'OptionSetSceneUnits'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSceneUnits'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetSceneUnits:94394503024032', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_scene_units.SetSceneUnits'>, 'config': {'title': 'SetSceneUnits'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_scene_units.SetSceneUnits'>>]}, 'ref': 'kittycad.models.set_scene_units.SetSceneUnits:94394502186720', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetSceneUnits', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_scene_units', 'schema': {'expected': ['set_scene_units'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSceneUnits', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSceneUnits, required=True), 'type': FieldInfo(annotation=Literal['set_scene_units'], required=False, default='set_scene_units')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed24da0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63cf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_scene_units",                                             },                                             expected_py: None,                                             name: "literal['set_scene_units']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec586e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetSceneUnits",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSceneUnits",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSceneUnits", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded60a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6070,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetSceneUnits",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec586e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetSceneUnits",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6100,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5f50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63cf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_scene_units": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd62a00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63cf0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_scene_units'",                                         name: "literal['set_scene_units']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_scene_units']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSceneUnits",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed24da0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetSceneUnits",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_scene_units.SetSceneUnits, type: Literal['set_scene_units'] = 'set_scene_units') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetSceneUnits

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSceneUnits, required=True), 'type': FieldInfo(annotation=Literal['set_scene_units'], required=False, default='set_scene_units')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_scene_units']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetSelectionFilter(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_selection_filter.SetSelectionFilter'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_selection_filter']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 627

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionFilter'>, 'config': {'title': 'OptionSetSelectionFilter'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionFilter'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionFilter:94394503042608', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_selection_filter.SetSelectionFilter'>, 'config': {'title': 'SetSelectionFilter'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_selection_filter.SetSelectionFilter'>>]}, 'ref': 'kittycad.models.set_selection_filter.SetSelectionFilter:94394502184800', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetSelectionFilter', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_selection_filter', 'schema': {'expected': ['set_selection_filter'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSelectionFilter', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSelectionFilter, required=True), 'type': FieldInfo(annotation=Literal['set_selection_filter'], required=False, default='set_selection_filter')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed29630,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec57f60,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetSelectionFilter",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63db0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_selection_filter",                                             },                                             expected_py: None,                                             name: "literal['set_selection_filter']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSelectionFilter",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSelectionFilter", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5770,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded57a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetSelectionFilter",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec57f60,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetSelectionFilter",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded56e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded57d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63db0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_selection_filter": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd68900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63db0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_selection_filter'",                                         name: "literal['set_selection_filter']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_selection_filter']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSelectionFilter",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed29630,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetSelectionFilter",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_selection_filter.SetSelectionFilter, type: Literal['set_selection_filter'] = 'set_selection_filter') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetSelectionFilter

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSelectionFilter, required=True), 'type': FieldInfo(annotation=Literal['set_selection_filter'], required=False, default='set_selection_filter')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_selection_filter']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetSelectionType(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_selection_type.SetSelectionType'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_selection_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 617

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionType'>, 'config': {'title': 'OptionSetSelectionType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionType'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetSelectionType:94394503033648', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_selection_type.SetSelectionType'>, 'config': {'title': 'SetSelectionType'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_selection_type.SetSelectionType'>>]}, 'ref': 'kittycad.models.set_selection_type.SetSelectionType:94394502222624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetSelectionType', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_selection_type', 'schema': {'expected': ['set_selection_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSelectionType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSelectionType, required=True), 'type': FieldInfo(annotation=Literal['set_selection_type'], required=False, default='set_selection_type')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed27330,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec61320,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetSelectionType",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63eb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_selection_type",                                             },                                             expected_py: None,                                             name: "literal['set_selection_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSelectionType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSelectionType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5cb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5da0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetSelectionType",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec61320,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetSelectionType",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5e00,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5b60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63eb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_selection_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd63940,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63eb0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_selection_type'",                                         name: "literal['set_selection_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_selection_type']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSelectionType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed27330,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetSelectionType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_selection_type.SetSelectionType, type: Literal['set_selection_type'] = 'set_selection_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetSelectionType

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetSelectionType, required=True), 'type': FieldInfo(annotation=Literal['set_selection_type'], required=False, default='set_selection_type')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_selection_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSetTool(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.set_tool.SetTool'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['set_tool']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 447

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSetTool'>, 'config': {'title': 'OptionSetTool'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSetTool'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSetTool:94394502442080', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.set_tool.SetTool'>, 'config': {'title': 'SetTool'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.set_tool.SetTool'>>]}, 'ref': 'kittycad.models.set_tool.SetTool:94394502221248', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SetTool', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'set_tool', 'schema': {'expected': ['set_tool'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetTool', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetTool, required=True), 'type': FieldInfo(annotation=Literal['set_tool'], required=False, default='set_tool')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec96c60,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec60dc0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SetTool",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee63f70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_tool",                                             },                                             expected_py: None,                                             name: "literal['set_tool']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetTool",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetTool", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6310,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6340,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SetTool",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec60dc0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SetTool",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6370,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded63a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee63f70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_tool": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd49780,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee63f70,                                                 ),                                             ],                                         },                                         expected_repr: "'set_tool'",                                         name: "literal['set_tool']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_tool']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetTool",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec96c60,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSetTool",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.set_tool.SetTool, type: Literal['set_tool'] = 'set_tool') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SetTool

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SetTool, required=True), 'type': FieldInfo(annotation=Literal['set_tool'], required=False, default='set_tool')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_tool']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSketchModeDisable(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.sketch_mode_disable.SketchModeDisable'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['sketch_mode_disable']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 467

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSketchModeDisable'>, 'config': {'title': 'OptionSketchModeDisable'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSketchModeDisable'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSketchModeDisable:94394502892224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.sketch_mode_disable.SketchModeDisable'>, 'config': {'title': 'SketchModeDisable'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.sketch_mode_disable.SketchModeDisable'>>]}, 'ref': 'kittycad.models.sketch_mode_disable.SketchModeDisable:94394502231856', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'SketchModeDisable', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'sketch_mode_disable', 'schema': {'expected': ['sketch_mode_disable'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSketchModeDisable', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SketchModeDisable, required=True), 'type': FieldInfo(annotation=Literal['sketch_mode_disable'], required=False, default='sketch_mode_disable')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed04ac0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec63730,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SketchModeDisable",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed64230,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "sketch_mode_disable",                                             },                                             expected_py: None,                                             name: "literal['sketch_mode_disable']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSketchModeDisable",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSketchModeDisable", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded6a00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded6a30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "SketchModeDisable",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec63730,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SketchModeDisable",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded6a60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded6a90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed64230,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "sketch_mode_disable": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd4b500,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed64230,                                                 ),                                             ],                                         },                                         expected_repr: "'sketch_mode_disable'",                                         name: "literal['sketch_mode_disable']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['sketch_mode_disable']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSketchModeDisable",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed04ac0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSketchModeDisable",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.sketch_mode_disable.SketchModeDisable, type: Literal['sketch_mode_disable'] = 'sketch_mode_disable') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SketchModeDisable

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SketchModeDisable, required=True), 'type': FieldInfo(annotation=Literal['sketch_mode_disable'], required=False, default='sketch_mode_disable')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['sketch_mode_disable']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid2DAddHole(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid2d_add_hole.Solid2dAddHole'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid2d_add_hole']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 377

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid2DAddHole'>, 'config': {'title': 'OptionSolid2DAddHole'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid2DAddHole'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid2DAddHole:94394502373344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid2d_add_hole.Solid2dAddHole'>, 'config': {'title': 'Solid2dAddHole'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid2d_add_hole.Solid2dAddHole'>>]}, 'ref': 'kittycad.models.solid2d_add_hole.Solid2dAddHole:94394502219744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Solid2dAddHole', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid2d_add_hole', 'schema': {'expected': ['solid2d_add_hole'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid2DAddHole', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid2dAddHole, required=True), 'type': FieldInfo(annotation=Literal['solid2d_add_hole'], required=False, default='solid2d_add_hole')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec85fe0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec607e0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid2dAddHole",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed64330,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid2d_add_hole",                                             },                                             expected_py: None,                                             name: "literal['solid2d_add_hole']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid2DAddHole",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid2DAddHole", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd365e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36640,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Solid2dAddHole",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec607e0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid2dAddHole",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36520,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36c70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed64330,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid2d_add_hole": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd08e80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed64330,                                                 ),                                             ],                                         },                                         expected_repr: "'solid2d_add_hole'",                                         name: "literal['solid2d_add_hole']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid2d_add_hole']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid2DAddHole",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec85fe0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid2DAddHole",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid2d_add_hole.Solid2dAddHole, type: Literal['solid2d_add_hole'] = 'solid2d_add_hole') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid2dAddHole

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid2dAddHole, required=True), 'type': FieldInfo(annotation=Literal['solid2d_add_hole'], required=False, default='solid2d_add_hole')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid2d_add_hole']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DFilletEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_fillet_edge.Solid3dFilletEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_fillet_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 387

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DFilletEdge'>, 'config': {'title': 'OptionSolid3DFilletEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DFilletEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DFilletEdge:94394502383088', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_fillet_edge.Solid3dFilletEdge'>, 'config': {'title': 'Solid3dFilletEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_fillet_edge.Solid3dFilletEdge'>>]}, 'ref': 'kittycad.models.solid3d_fillet_edge.Solid3dFilletEdge:94394502230768', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Solid3dFilletEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_fillet_edge', 'schema': {'expected': ['solid3d_fillet_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DFilletEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dFilletEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_fillet_edge'], required=False, default='solid3d_fillet_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec885f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec632f0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dFilletEdge",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed643f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_fillet_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_fillet_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DFilletEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DFilletEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35c50,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd36ac0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Solid3dFilletEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec632f0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dFilletEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd36b20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd36eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed643f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_fillet_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd00040,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed643f0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_fillet_edge'",                                         name: "literal['solid3d_fillet_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_fillet_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DFilletEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec885f0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DFilletEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_fillet_edge.Solid3dFilletEdge, type: Literal['solid3d_fillet_edge'] = 'solid3d_fillet_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dFilletEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dFilletEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_fillet_edge'], required=False, default='solid3d_fillet_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_fillet_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllEdgeFaces(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_all_edge_faces.Solid3dGetAllEdgeFaces'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_all_edge_faces']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 959

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllEdgeFaces'>, 'config': {'title': 'OptionSolid3DGetAllEdgeFaces'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllEdgeFaces'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllEdgeFaces:94394503623440', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_all_edge_faces.Solid3dGetAllEdgeFaces'>, 'config': {'title': 'Solid3dGetAllEdgeFaces'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_all_edge_faces.Solid3dGetAllEdgeFaces'>>]}, 'ref': 'kittycad.models.solid3d_get_all_edge_faces.Solid3dGetAllEdgeFaces:94394502245504', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'faces': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetAllEdgeFaces', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_all_edge_faces', 'schema': {'expected': ['solid3d_get_all_edge_faces'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetAllEdgeFaces', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetAllEdgeFaces, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_edge_faces'], required=False, default='solid3d_get_all_edge_faces')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedb7310,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78850,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_all_edge_faces",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_all_edge_faces']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec66c80,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "faces": SerField {                                                     key_py: Py(                                                         0x00007f1ebe5f55f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetAllEdgeFaces",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetAllEdgeFaces",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetAllEdgeFaces", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda11a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda11d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "faces",                                                 lookup_key: Simple {                                                     key: "faces",                                                     py_key: Py(                                                         0x00007f1ebdda1140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "faces",                                                                 Py(                                                                     0x00007f1ebdda1170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe5f55f0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetAllEdgeFaces",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec66c80,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetAllEdgeFaces",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1200,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1230,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78850,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_all_edge_faces": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddcad80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78850,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_all_edge_faces'",                                         name: "literal['solid3d_get_all_edge_faces']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_all_edge_faces']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetAllEdgeFaces",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedb7310,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetAllEdgeFaces",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_all_edge_faces.Solid3dGetAllEdgeFaces, type: Literal['solid3d_get_all_edge_faces'] = 'solid3d_get_all_edge_faces') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetAllEdgeFaces

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetAllEdgeFaces, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_edge_faces'], required=False, default='solid3d_get_all_edge_faces')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_all_edge_faces']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllOppositeEdges(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_all_opposite_edges.Solid3dGetAllOppositeEdges'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_all_opposite_edges']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 969

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllOppositeEdges'>, 'config': {'title': 'OptionSolid3DGetAllOppositeEdges'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllOppositeEdges'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetAllOppositeEdges:94394503635792', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_all_opposite_edges.Solid3dGetAllOppositeEdges'>, 'config': {'title': 'Solid3dGetAllOppositeEdges'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_all_opposite_edges.Solid3dGetAllOppositeEdges'>>]}, 'ref': 'kittycad.models.solid3d_get_all_opposite_edges.Solid3dGetAllOppositeEdges:94394502243360', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edges': {'metadata': {}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetAllOppositeEdges', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_all_opposite_edges', 'schema': {'expected': ['solid3d_get_all_opposite_edges'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetAllOppositeEdges', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetAllOppositeEdges, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_opposite_edges'], required=False, default='solid3d_get_all_opposite_edges')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedba350,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec66420,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "edges": SerField {                                                     key_py: Py(                                                         0x00007f1ec28bb3f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Str(                                                                     StrSerializer,                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[str]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetAllOppositeEdges",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee788a0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_all_opposite_edges",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_all_opposite_edges']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetAllOppositeEdges",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetAllOppositeEdges", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1590,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda15c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "edges",                                                 lookup_key: Simple {                                                     key: "edges",                                                     py_key: Py(                                                         0x00007f1ebdda1530,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "edges",                                                                 Py(                                                                     0x00007f1ebdda1560,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec28bb3f0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetAllOppositeEdges",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec66420,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetAllOppositeEdges",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda15f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1620,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee788a0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_all_opposite_edges": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddcbe40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee788a0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_all_opposite_edges'",                                         name: "literal['solid3d_get_all_opposite_edges']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_all_opposite_edges']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetAllOppositeEdges",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedba350,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetAllOppositeEdges",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_all_opposite_edges.Solid3dGetAllOppositeEdges, type: Literal['solid3d_get_all_opposite_edges'] = 'solid3d_get_all_opposite_edges') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetAllOppositeEdges

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetAllOppositeEdges, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_opposite_edges'], required=False, default='solid3d_get_all_opposite_edges')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_all_opposite_edges']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetCommonEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_common_edge.Solid3dGetCommonEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_common_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1009

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetCommonEdge'>, 'config': {'title': 'OptionSolid3DGetCommonEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetCommonEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetCommonEdge:94394503686496', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_common_edge.Solid3dGetCommonEdge'>, 'config': {'title': 'Solid3dGetCommonEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_common_edge.Solid3dGetCommonEdge'>>]}, 'ref': 'kittycad.models.solid3d_get_common_edge.Solid3dGetCommonEdge:94394502671312', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetCommonEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_common_edge', 'schema': {'expected': ['solid3d_get_common_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetCommonEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetCommonEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_common_edge'], required=False, default='solid3d_get_common_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedc6960,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed64630,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_common_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_common_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eeccebd0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "edge": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb648d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetCommonEdge",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetCommonEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetCommonEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded5a70,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded5740,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "edge",                                                 lookup_key: Simple {                                                     key: "edge",                                                     py_key: Py(                                                         0x00007f1ebded7360,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "edge",                                                                 Py(                                                                     0x00007f1ebded56b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb648d0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetCommonEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eeccebd0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetCommonEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded5a10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded5920,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed64630,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_common_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf43840,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed64630,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_common_edge'",                                         name: "literal['solid3d_get_common_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_common_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetCommonEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedc6960,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetCommonEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_common_edge.Solid3dGetCommonEdge, type: Literal['solid3d_get_common_edge'] = 'solid3d_get_common_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetCommonEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetCommonEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_common_edge'], required=False, default='solid3d_get_common_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_common_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetExtrusionFaceInfo(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_extrusion_face_info.Solid3dGetExtrusionFaceInfo'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_extrusion_face_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1391

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetExtrusionFaceInfo'>, 'config': {'title': 'OptionSolid3DGetExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetExtrusionFaceInfo:94394504197920', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_extrusion_face_info.Solid3dGetExtrusionFaceInfo'>, 'config': {'title': 'Solid3dGetExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_extrusion_face_info.Solid3dGetExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.solid3d_get_extrusion_face_info.Solid3dGetExtrusionFaceInfo:94394502678704', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'faces': {'metadata': {}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo'>, 'config': {'title': 'ExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.extrusion_face_info.ExtrusionFaceInfo:94394495105664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'cap': {'metadata': {}, 'schema': {'cls': <enum 'ExtrusionFaceCapType'>, 'members': [ExtrusionFaceCapType.NONE, ExtrusionFaceCapType.TOP, ExtrusionFaceCapType.BOTTOM, ExtrusionFaceCapType.BOTH], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.extrusion_face_cap_type.ExtrusionFaceCapType:94394495082704', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'curve_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'face_id': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'ExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_extrusion_face_info', 'schema': {'expected': ['solid3d_get_extrusion_face_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetExtrusionFaceInfo, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_extrusion_face_info'], required=False, default='solid3d_get_extrusion_face_info')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee43720,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78940,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_extrusion_face_info",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_extrusion_face_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd08b0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "faces": SerField {                                                     key_py: Py(                                                         0x00007f1ebe5f55f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         List(                                                             ListSerializer {                                                                 item_serializer: Model(                                                                     ModelSerializer {                                                                         class: Py(                                                                             0x000055d9ee597a80,                                                                         ),                                                                         serializer: Fields(                                                                             GeneralFieldsSerializer {                                                                                 fields: {                                                                                     "cap": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ec0b2f8a0,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             Enum(                                                                                                 EnumSerializer {                                                                                                     class: Py(                                                                                                         0x000055d9ee5920d0,                                                                                                     ),                                                                                                     serializer: Some(                                                                                                         Str(                                                                                                             StrSerializer,                                                                                                         ),                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "curve_id": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ebe437bf0,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             WithDefault(                                                                                                 WithDefaultSerializer {                                                                                                     default: Default(                                                                                                         Py(                                                                                                             0x00007f1ec2ed0400,                                                                                                         ),                                                                                                     ),                                                                                                     serializer: Nullable(                                                                                                         NullableSerializer {                                                                                                             serializer: Str(                                                                                                                 StrSerializer,                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                     "face_id": SerField {                                                                                         key_py: Py(                                                                                             0x00007f1ebeddda10,                                                                                         ),                                                                                         alias: None,                                                                                         alias_py: None,                                                                                         serializer: Some(                                                                                             WithDefault(                                                                                                 WithDefaultSerializer {                                                                                                     default: Default(                                                                                                         Py(                                                                                                             0x00007f1ec2ed0400,                                                                                                         ),                                                                                                     ),                                                                                                     serializer: Nullable(                                                                                                         NullableSerializer {                                                                                                             serializer: Str(                                                                                                                 StrSerializer,                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         ),                                                                                         required: true,                                                                                     },                                                                                 },                                                                                 computed_fields: Some(                                                                                     ComputedFields(                                                                                         [],                                                                                     ),                                                                                 ),                                                                                 mode: SimpleDict,                                                                                 extra_serializer: None,                                                                                 filter: SchemaFilter {                                                                                     include: None,                                                                                     exclude: None,                                                                                 },                                                                                 required_fields: 3,                                                                             },                                                                         ),                                                                         has_extra: false,                                                                         root_model: false,                                                                         name: "ExtrusionFaceInfo",                                                                     },                                                                 ),                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 name: "list[ExtrusionFaceInfo]",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetExtrusionFaceInfo",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetExtrusionFaceInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetExtrusionFaceInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda09f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0570,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "faces",                                                 lookup_key: Simple {                                                     key: "faces",                                                     py_key: Py(                                                         0x00007f1ebdda0c60,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "faces",                                                                 Py(                                                                     0x00007f1ebdda0990,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebe5f55f0,                                                 ),                                                 validator: List(                                                     ListValidator {                                                         strict: false,                                                         item_validator: Some(                                                             Model(                                                                 ModelValidator {                                                                     revalidate: Never,                                                                     validator: ModelFields(                                                                         ModelFieldsValidator {                                                                             fields: [                                                                                 Field {                                                                                     name: "cap",                                                                                     lookup_key: Simple {                                                                                         key: "cap",                                                                                         py_key: Py(                                                                                             0x00007f1ebdda0b10,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "cap",                                                                                                     Py(                                                                                                         0x00007f1ebdda0db0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ec0b2f8a0,                                                                                     ),                                                                                     validator: StrEnum(                                                                                         EnumValidator {                                                                                             phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                             class: Py(                                                                                                 0x000055d9ee5920d0,                                                                                             ),                                                                                             lookup: LiteralLookup {                                                                                                 expected_bool: None,                                                                                                 expected_int: None,                                                                                                 expected_str: Some(                                                                                                     {                                                                                                         "both": 3,                                                                                                         "none": 0,                                                                                                         "top": 1,                                                                                                         "bottom": 2,                                                                                                     },                                                                                                 ),                                                                                                 expected_py_dict: None,                                                                                                 expected_py_values: None,                                                                                                 expected_py_primitives: Some(                                                                                                     Py(                                                                                                         0x00007f1ebdde9200,                                                                                                     ),                                                                                                 ),                                                                                                 values: [                                                                                                     Py(                                                                                                         0x00007f1ebe43c230,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebe43c170,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebe43c290,                                                                                                     ),                                                                                                     Py(                                                                                                         0x00007f1ebe43c2f0,                                                                                                     ),                                                                                                 ],                                                                                             },                                                                                             missing: None,                                                                                             expected_repr: "'none', 'top', 'bottom' or 'both'",                                                                                             strict: false,                                                                                             class_repr: "ExtrusionFaceCapType",                                                                                             name: "str-enum[ExtrusionFaceCapType]",                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "curve_id",                                                                                     lookup_key: Simple {                                                                                         key: "curve_id",                                                                                         py_key: Py(                                                                                             0x00007f1ebdde90b0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "curve_id",                                                                                                     Py(                                                                                                         0x00007f1ebdde8930,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ebe437bf0,                                                                                     ),                                                                                     validator: WithDefault(                                                                                         WithDefaultValidator {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             on_error: Raise,                                                                                             validator: Nullable(                                                                                                 NullableValidator {                                                                                                     validator: Str(                                                                                                         StrValidator {                                                                                                             strict: false,                                                                                                             coerce_numbers_to_str: false,                                                                                                         },                                                                                                     ),                                                                                                     name: "nullable[str]",                                                                                                 },                                                                                             ),                                                                                             validate_default: false,                                                                                             copy_default: false,                                                                                             name: "default[nullable[str]]",                                                                                             undefined: Py(                                                                                                 0x00007f1ec0cae3d0,                                                                                             ),                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                                 Field {                                                                                     name: "face_id",                                                                                     lookup_key: Simple {                                                                                         key: "face_id",                                                                                         py_key: Py(                                                                                             0x00007f1ebdda0cf0,                                                                                         ),                                                                                         path: LookupPath(                                                                                             [                                                                                                 S(                                                                                                     "face_id",                                                                                                     Py(                                                                                                         0x00007f1ebdda09c0,                                                                                                     ),                                                                                                 ),                                                                                             ],                                                                                         ),                                                                                     },                                                                                     name_py: Py(                                                                                         0x00007f1ebeddda10,                                                                                     ),                                                                                     validator: WithDefault(                                                                                         WithDefaultValidator {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             on_error: Raise,                                                                                             validator: Nullable(                                                                                                 NullableValidator {                                                                                                     validator: Str(                                                                                                         StrValidator {                                                                                                             strict: false,                                                                                                             coerce_numbers_to_str: false,                                                                                                         },                                                                                                     ),                                                                                                     name: "nullable[str]",                                                                                                 },                                                                                             ),                                                                                             validate_default: false,                                                                                             copy_default: false,                                                                                             name: "default[nullable[str]]",                                                                                             undefined: Py(                                                                                                 0x00007f1ec0cae3d0,                                                                                             ),                                                                                         },                                                                                     ),                                                                                     frozen: false,                                                                                 },                                                                             ],                                                                             model_name: "ExtrusionFaceInfo",                                                                             extra_behavior: Ignore,                                                                             extras_validator: None,                                                                             strict: false,                                                                             from_attributes: false,                                                                             loc_by_alias: true,                                                                         },                                                                     ),                                                                     class: Py(                                                                         0x000055d9ee597a80,                                                                     ),                                                                     generic_origin: None,                                                                     post_init: None,                                                                     frozen: false,                                                                     custom_init: false,                                                                     root_model: false,                                                                     undefined: Py(                                                                         0x00007f1ec0cae3d0,                                                                     ),                                                                     name: "ExtrusionFaceInfo",                                                                 },                                                             ),                                                         ),                                                         min_length: None,                                                         max_length: None,                                                         name: OnceLock(                                                             <uninit>,                                                         ),                                                         fail_fast: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetExtrusionFaceInfo",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd08b0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetExtrusionFaceInfo",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0270,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0600,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78940,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_extrusion_face_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde9140,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78940,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_extrusion_face_info'",                                         name: "literal['solid3d_get_extrusion_face_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_extrusion_face_info']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetExtrusionFaceInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee43720,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetExtrusionFaceInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_extrusion_face_info.Solid3dGetExtrusionFaceInfo, type: Literal['solid3d_get_extrusion_face_info'] = 'solid3d_get_extrusion_face_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetExtrusionFaceInfo

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetExtrusionFaceInfo, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_extrusion_face_info'], required=False, default='solid3d_get_extrusion_face_info')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_extrusion_face_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetNextAdjacentEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_next_adjacent_edge.Solid3dGetNextAdjacentEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_next_adjacent_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 989

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetNextAdjacentEdge'>, 'config': {'title': 'OptionSolid3DGetNextAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetNextAdjacentEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetNextAdjacentEdge:94394503659904', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_next_adjacent_edge.Solid3dGetNextAdjacentEdge'>, 'config': {'title': 'Solid3dGetNextAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_next_adjacent_edge.Solid3dGetNextAdjacentEdge'>>]}, 'ref': 'kittycad.models.solid3d_get_next_adjacent_edge.Solid3dGetNextAdjacentEdge:94394502694336', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetNextAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_next_adjacent_edge', 'schema': {'expected': ['solid3d_get_next_adjacent_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetNextAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetNextAdjacentEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_next_adjacent_edge'], required=False, default='solid3d_get_next_adjacent_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedc0180,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee789e0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_next_adjacent_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_next_adjacent_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd45c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "edge": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb648d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetNextAdjacentEdge",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetNextAdjacentEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetNextAdjacentEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1d40,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1d70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "edge",                                                 lookup_key: Simple {                                                     key: "edge",                                                     py_key: Py(                                                         0x00007f1ebdda1ce0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "edge",                                                                 Py(                                                                     0x00007f1ebdda1d10,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb648d0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetNextAdjacentEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd45c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetNextAdjacentEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1da0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1dd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee789e0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_next_adjacent_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddd5e80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee789e0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_next_adjacent_edge'",                                         name: "literal['solid3d_get_next_adjacent_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_next_adjacent_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetNextAdjacentEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedc0180,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetNextAdjacentEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_next_adjacent_edge.Solid3dGetNextAdjacentEdge, type: Literal['solid3d_get_next_adjacent_edge'] = 'solid3d_get_next_adjacent_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetNextAdjacentEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetNextAdjacentEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_next_adjacent_edge'], required=False, default='solid3d_get_next_adjacent_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_next_adjacent_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetOppositeEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_opposite_edge.Solid3dGetOppositeEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_opposite_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 979

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetOppositeEdge'>, 'config': {'title': 'OptionSolid3DGetOppositeEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetOppositeEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetOppositeEdge:94394503648256', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_opposite_edge.Solid3dGetOppositeEdge'>, 'config': {'title': 'Solid3dGetOppositeEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_opposite_edge.Solid3dGetOppositeEdge'>>]}, 'ref': 'kittycad.models.solid3d_get_opposite_edge.Solid3dGetOppositeEdge:94394502701728', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge': {'metadata': {}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetOppositeEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_opposite_edge', 'schema': {'expected': ['solid3d_get_opposite_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetOppositeEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetOppositeEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_opposite_edge'], required=False, default='solid3d_get_opposite_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedbd400,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78a80,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_opposite_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_opposite_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd62a0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "edge": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb648d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Str(                                                             StrSerializer,                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetOppositeEdge",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetOppositeEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetOppositeEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda1950,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1980,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "edge",                                                 lookup_key: Simple {                                                     key: "edge",                                                     py_key: Py(                                                         0x00007f1ebdda18f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "edge",                                                                 Py(                                                                     0x00007f1ebdda1920,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb648d0,                                                 ),                                                 validator: Str(                                                     StrValidator {                                                         strict: false,                                                         coerce_numbers_to_str: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetOppositeEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd62a0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetOppositeEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda19b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda19e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78a80,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_opposite_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddd4ec0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78a80,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_opposite_edge'",                                         name: "literal['solid3d_get_opposite_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_opposite_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetOppositeEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedbd400,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetOppositeEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_opposite_edge.Solid3dGetOppositeEdge, type: Literal['solid3d_get_opposite_edge'] = 'solid3d_get_opposite_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetOppositeEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetOppositeEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_opposite_edge'], required=False, default='solid3d_get_opposite_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_opposite_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetPrevAdjacentEdge(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_get_prev_adjacent_edge.Solid3dGetPrevAdjacentEdge'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_get_prev_adjacent_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 999

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetPrevAdjacentEdge'>, 'config': {'title': 'OptionSolid3DGetPrevAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetPrevAdjacentEdge'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DGetPrevAdjacentEdge:94394503673232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_get_prev_adjacent_edge.Solid3dGetPrevAdjacentEdge'>, 'config': {'title': 'Solid3dGetPrevAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_get_prev_adjacent_edge.Solid3dGetPrevAdjacentEdge'>>]}, 'ref': 'kittycad.models.solid3d_get_prev_adjacent_edge.Solid3dGetPrevAdjacentEdge:94394502708128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'Solid3dGetPrevAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_get_prev_adjacent_edge', 'schema': {'expected': ['solid3d_get_prev_adjacent_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetPrevAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetPrevAdjacentEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_prev_adjacent_edge'], required=False, default='solid3d_get_prev_adjacent_edge')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedc3590,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd7ba0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "edge": SerField {                                                     key_py: Py(                                                         0x00007f1ebeb648d0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007f1ec2ed0400,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dGetPrevAdjacentEdge",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebee78ad0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_prev_adjacent_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_prev_adjacent_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetPrevAdjacentEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetPrevAdjacentEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2130,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2160,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "edge",                                                 lookup_key: Simple {                                                     key: "edge",                                                     py_key: Py(                                                         0x00007f1ebdda20d0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "edge",                                                                 Py(                                                                     0x00007f1ebdda2100,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebeb648d0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007f1ec2ed0400,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Str(                                                                     StrValidator {                                                                         strict: false,                                                                         coerce_numbers_to_str: false,                                                                     },                                                                 ),                                                                 name: "nullable[str]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[str]]",                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Solid3dGetPrevAdjacentEdge",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd7ba0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dGetPrevAdjacentEdge",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda2190,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda21c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebee78ad0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_prev_adjacent_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddd6f80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebee78ad0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_prev_adjacent_edge'",                                         name: "literal['solid3d_get_prev_adjacent_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_prev_adjacent_edge']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetPrevAdjacentEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedc3590,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DGetPrevAdjacentEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_get_prev_adjacent_edge.Solid3dGetPrevAdjacentEdge, type: Literal['solid3d_get_prev_adjacent_edge'] = 'solid3d_get_prev_adjacent_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dGetPrevAdjacentEdge

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dGetPrevAdjacentEdge, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_prev_adjacent_edge'], required=False, default='solid3d_get_prev_adjacent_edge')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_prev_adjacent_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSolid3DShellFace(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.solid3d_shell_face.Solid3dShellFace'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['solid3d_shell_face']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 215

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DShellFace'>, 'config': {'title': 'OptionSolid3DShellFace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DShellFace'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSolid3DShellFace:94394502576736', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.solid3d_shell_face.Solid3dShellFace'>, 'config': {'title': 'Solid3dShellFace'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.solid3d_shell_face.Solid3dShellFace'>>]}, 'ref': 'kittycad.models.solid3d_shell_face.Solid3dShellFace:94394502715520', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Solid3dShellFace', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'solid3d_shell_face', 'schema': {'expected': ['solid3d_shell_face'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DShellFace', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dShellFace, required=True), 'type': FieldInfo(annotation=Literal['solid3d_shell_face'], required=False, default='solid3d_shell_face')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecb7a60,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd9880,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Solid3dShellFace",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed64970,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_shell_face",                                             },                                             expected_py: None,                                             name: "literal['solid3d_shell_face']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DShellFace",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DShellFace", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9a1c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9adf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Solid3dShellFace",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd9880,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Solid3dShellFace",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9b450,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9aaf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed64970,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_shell_face": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1d280,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed64970,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_shell_face'",                                         name: "literal['solid3d_shell_face']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_shell_face']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DShellFace",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecb7a60,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSolid3DShellFace",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.solid3d_shell_face.Solid3dShellFace, type: Literal['solid3d_shell_face'] = 'solid3d_shell_face') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Solid3dShellFace

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Solid3dShellFace, required=True), 'type': FieldInfo(annotation=Literal['solid3d_shell_face'], required=False, default='solid3d_shell_face')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_shell_face']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionStartPath(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.start_path.StartPath'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['start_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 155

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionStartPath'>, 'config': {'title': 'OptionStartPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionStartPath'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionStartPath:94394502066480', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.start_path.StartPath'>, 'config': {'title': 'StartPath'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.start_path.StartPath'>>]}, 'ref': 'kittycad.models.start_path.StartPath:94394502713152', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'StartPath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'start_path', 'schema': {'expected': ['start_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionStartPath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=StartPath, required=True), 'type': FieldInfo(annotation=Literal['start_path'], required=False, default='start_path')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec3b130,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd8f40,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "StartPath",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed64c30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "start_path",                                             },                                             expected_py: None,                                             name: "literal['start_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionStartPath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionStartPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34a80,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd348a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "StartPath",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd8f40,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "StartPath",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd34a20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34c30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed64c30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "start_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd22680,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed64c30,                                                 ),                                             ],                                         },                                         expected_repr: "'start_path'",                                         name: "literal['start_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['start_path']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionStartPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec3b130,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionStartPath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.start_path.StartPath, type: Literal['start_path'] = 'start_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: StartPath

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=StartPath, required=True), 'type': FieldInfo(annotation=Literal['start_path'], required=False, default='start_path')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['start_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSurfaceArea(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.surface_area.SurfaceArea'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['surface_area']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1261

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSurfaceArea'>, 'config': {'title': 'OptionSurfaceArea'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSurfaceArea'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSurfaceArea:94394504031760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.surface_area.SurfaceArea'>, 'config': {'title': 'SurfaceArea'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.surface_area.SurfaceArea'>>]}, 'ref': 'kittycad.models.surface_area.SurfaceArea:94394502752848', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'output_unit': {'metadata': {}, 'schema': {'cls': <enum 'UnitArea'>, 'members': [UnitArea.CM2, UnitArea.DM2, UnitArea.FT2, UnitArea.IN2, UnitArea.KM2, UnitArea.M2, UnitArea.MM2, UnitArea.YD2], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_area.UnitArea:94394491849504', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'surface_area': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'SurfaceArea', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'surface_area', 'schema': {'expected': ['surface_area'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSurfaceArea', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SurfaceArea, required=True), 'type': FieldInfo(annotation=Literal['surface_area'], required=False, default='surface_area')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee1ae10,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed651f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "surface_area",                                             },                                             expected_py: None,                                             name: "literal['surface_area']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eece2a50,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "surface_area": SerField {                                                     key_py: Py(                                                         0x00007f1ebed651f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "output_unit": SerField {                                                     key_py: Py(                                                         0x00007f1ebebb86b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee27cb20,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "SurfaceArea",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSurfaceArea",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSurfaceArea", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda0c00,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda0bd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "output_unit",                                                 lookup_key: Simple {                                                     key: "output_unit",                                                     py_key: Py(                                                         0x00007f1ebdde9830,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "output_unit",                                                                 Py(                                                                     0x00007f1ebdde97f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebebb86b0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee27cb20,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "mm2": 6,                                                                     "ft2": 2,                                                                     "km2": 4,                                                                     "in2": 3,                                                                     "cm2": 0,                                                                     "dm2": 1,                                                                     "m2": 5,                                                                     "yd2": 7,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdde9780,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe5f15b0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1610,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1670,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f16d0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1730,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1790,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f17f0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1850,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'cm2', 'dm2', 'ft2', 'in2', 'km2', 'm2', 'mm2' or 'yd2'",                                                         strict: false,                                                         class_repr: "UnitArea",                                                         name: "str-enum[UnitArea]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "surface_area",                                                 lookup_key: Simple {                                                     key: "surface_area",                                                     py_key: Py(                                                         0x00007f1ebdde9870,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "surface_area",                                                                 Py(                                                                     0x00007f1ebdde98b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebed651f0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "SurfaceArea",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eece2a50,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "SurfaceArea",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda0cc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda0c90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed651f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "surface_area": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde9900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed651f0,                                                 ),                                             ],                                         },                                         expected_repr: "'surface_area'",                                         name: "literal['surface_area']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['surface_area']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSurfaceArea",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee1ae10,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSurfaceArea",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.surface_area.SurfaceArea, type: Literal['surface_area'] = 'surface_area') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: SurfaceArea

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=SurfaceArea, required=True), 'type': FieldInfo(annotation=Literal['surface_area'], required=False, default='surface_area')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['surface_area']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionSweep(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.sweep.Sweep'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['sweep']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 195

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionSweep'>, 'config': {'title': 'OptionSweep'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionSweep'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionSweep:94394502558112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.sweep.Sweep'>, 'config': {'title': 'Sweep'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.sweep.Sweep'>>]}, 'ref': 'kittycad.models.sweep.Sweep:94394502687920', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'Sweep', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'sweep', 'schema': {'expected': ['sweep'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSweep', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Sweep, required=True), 'type': FieldInfo(annotation=Literal['sweep'], required=False, default='sweep')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eecb31a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecd2cb0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Sweep",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebf2881e0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "sweep",                                             },                                             expected_py: None,                                             name: "literal['sweep']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSweep",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSweep", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebde9bd20,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebde9bcc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "Sweep",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecd2cb0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Sweep",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebde9bb10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebde9bae0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebf2881e0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "sweep": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd1ee80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebf2881e0,                                                 ),                                             ],                                         },                                         expected_repr: "'sweep'",                                         name: "literal['sweep']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['sweep']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSweep",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eecb31a0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionSweep",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.sweep.Sweep, type: Literal['sweep'] = 'sweep') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Sweep

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Sweep, required=True), 'type': FieldInfo(annotation=Literal['sweep'], required=False, default='sweep')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['sweep']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionTakeSnapshot(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.take_snapshot.TakeSnapshot'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['take_snapshot']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1079

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionTakeSnapshot'>, 'config': {'title': 'OptionTakeSnapshot'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionTakeSnapshot'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionTakeSnapshot:94394503750432', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.take_snapshot.TakeSnapshot'>, 'config': {'title': 'TakeSnapshot'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.take_snapshot.TakeSnapshot'>>]}, 'ref': 'kittycad.models.take_snapshot.TakeSnapshot:94394502735568', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'contents': {'metadata': {}, 'schema': {'function': {'function': <bound method Base64Data.validate of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'no-info'}, 'schema': {'choices': [{'type': 'str'}, {'type': 'bytes'}], 'type': 'union'}, 'serialization': {'function': <bound method Base64Data.serialize of <class 'kittycad.models.base64data.Base64Data'>>, 'type': 'function-plain'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'TakeSnapshot', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'take_snapshot', 'schema': {'expected': ['take_snapshot'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionTakeSnapshot', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=TakeSnapshot, required=True), 'type': FieldInfo(annotation=Literal['take_snapshot'], required=False, default='take_snapshot')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eedd6320,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecde6d0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "contents": SerField {                                                     key_py: Py(                                                         0x00007f1ec28f9e30,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Function(                                                             FunctionPlainSerializer {                                                                 func: Py(                                                                     0x00007f1ebde0f4c0,                                                                 ),                                                                 name: "plain_function[serialize]",                                                                 function_name: "serialize",                                                                 return_serializer: Any(                                                                     AnySerializer,                                                                 ),                                                                 fallback_serializer: None,                                                                 when_used: Always,                                                                 is_field_serializer: false,                                                                 info_arg: false,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "TakeSnapshot",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed65270,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "take_snapshot",                                             },                                             expected_py: None,                                             name: "literal['take_snapshot']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionTakeSnapshot",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionTakeSnapshot", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2010,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda1fe0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "contents",                                                 lookup_key: Simple {                                                     key: "contents",                                                     py_key: Py(                                                         0x00007f1ebde047b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "contents",                                                                 Py(                                                                     0x00007f1ebde04730,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec28f9e30,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Union(                                                             UnionValidator {                                                                 mode: Smart,                                                                 choices: [                                                                     (                                                                         Str(                                                                             StrValidator {                                                                                 strict: false,                                                                                 coerce_numbers_to_str: false,                                                                             },                                                                         ),                                                                         None,                                                                     ),                                                                     (                                                                         Bytes(                                                                             BytesValidator {                                                                                 strict: false,                                                                                 bytes_mode: ValBytesMode {                                                                                     ser: Utf8,                                                                                 },                                                                             },                                                                         ),                                                                         None,                                                                     ),                                                                 ],                                                                 custom_error: None,                                                                 strict: false,                                                                 name: "union[str,bytes]",                                                             },                                                         ),                                                         func: Py(                                                             0x00007f1ebde0f8c0,                                                         ),                                                         config: Py(                                                             0x00007f1ebde064c0,                                                         ),                                                         name: "function-after[validate(), union[str,bytes]]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "TakeSnapshot",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecde6d0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "TakeSnapshot",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda1f80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda1fb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed65270,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "take_snapshot": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebde04900,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed65270,                                                 ),                                             ],                                         },                                         expected_repr: "'take_snapshot'",                                         name: "literal['take_snapshot']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['take_snapshot']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionTakeSnapshot",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eedd6320,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionTakeSnapshot",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.take_snapshot.TakeSnapshot, type: Literal['take_snapshot'] = 'take_snapshot') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: TakeSnapshot

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=TakeSnapshot, required=True), 'type': FieldInfo(annotation=Literal['take_snapshot'], required=False, default='take_snapshot')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['take_snapshot']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionUpdateAnnotation(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.update_annotation.UpdateAnnotation'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['update_annotation']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 327

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionUpdateAnnotation'>, 'config': {'title': 'OptionUpdateAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionUpdateAnnotation'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionUpdateAnnotation:94394502326368', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.update_annotation.UpdateAnnotation'>, 'config': {'title': 'UpdateAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.update_annotation.UpdateAnnotation'>>]}, 'ref': 'kittycad.models.update_annotation.UpdateAnnotation:94394502727328', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'UpdateAnnotation', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'update_annotation', 'schema': {'expected': ['update_annotation'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionUpdateAnnotation', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=UpdateAnnotation, required=True), 'type': FieldInfo(annotation=Literal['update_annotation'], required=False, default='update_annotation')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eec7a860,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecdc6a0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {},                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 0,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "UpdateAnnotation",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed86ff0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "update_annotation",                                             },                                             expected_py: None,                                             name: "literal['update_annotation']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionUpdateAnnotation",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionUpdateAnnotation", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd35680,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd35590,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [],                                         model_name: "UpdateAnnotation",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecdc6a0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "UpdateAnnotation",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd35710,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd35290,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed86ff0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "update_annotation": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdf30100,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed86ff0,                                                 ),                                             ],                                         },                                         expected_repr: "'update_annotation'",                                         name: "literal['update_annotation']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['update_annotation']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionUpdateAnnotation",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eec7a860,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionUpdateAnnotation",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.update_annotation.UpdateAnnotation, type: Literal['update_annotation'] = 'update_annotation') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: UpdateAnnotation

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=UpdateAnnotation, required=True), 'type': FieldInfo(annotation=Literal['update_annotation'], required=False, default='update_annotation')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['update_annotation']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionViewIsometric(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.view_isometric.ViewIsometric'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['view_isometric']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 889

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionViewIsometric'>, 'config': {'title': 'OptionViewIsometric'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionViewIsometric'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionViewIsometric:94394503520496', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.view_isometric.ViewIsometric'>, 'config': {'title': 'ViewIsometric'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.view_isometric.ViewIsometric'>>]}, 'ref': 'kittycad.models.view_isometric.ViewIsometric:94394502732736', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'ViewIsometric', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'view_isometric', 'schema': {'expected': ['view_isometric'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionViewIsometric', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ViewIsometric, required=True), 'type': FieldInfo(annotation=Literal['view_isometric'], required=False, default='view_isometric')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed9e0f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed87670,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "view_isometric",                                             },                                             expected_py: None,                                             name: "literal['view_isometric']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eecddbc0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ViewIsometric",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionViewIsometric",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionViewIsometric", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdd34f90,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdd34fc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebddbb9b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebddbb9f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebdd35980,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebdd34ae0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebdd349f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebdd348d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebddbb8f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebddbb8b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebdd345d0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebdd34d50,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebddbb970,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebddbb930,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebdd34cc0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebdd35bc0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebdd35380,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebdd35050,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ViewIsometric",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eecddbc0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ViewIsometric",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdd347b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdd34d80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed87670,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "view_isometric": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebddbba40,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed87670,                                                 ),                                             ],                                         },                                         expected_repr: "'view_isometric'",                                         name: "literal['view_isometric']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['view_isometric']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionViewIsometric",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed9e0f0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionViewIsometric",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.view_isometric.ViewIsometric, type: Literal['view_isometric'] = 'view_isometric') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ViewIsometric

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ViewIsometric, required=True), 'type': FieldInfo(annotation=Literal['view_isometric'], required=False, default='view_isometric')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['view_isometric']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionVolume(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.volume.Volume'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['volume']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 1241

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionVolume'>, 'config': {'title': 'OptionVolume'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionVolume'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionVolume:94394504004944', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.volume.Volume'>, 'config': {'title': 'Volume'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.volume.Volume'>>]}, 'ref': 'kittycad.models.volume.Volume:94394502466208', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'output_unit': {'metadata': {}, 'schema': {'cls': <enum 'UnitVolume'>, 'members': [UnitVolume.CM3, UnitVolume.FT3, UnitVolume.IN3, UnitVolume.M3, UnitVolume.YD3, UnitVolume.USFLOZ, UnitVolume.USGAL, UnitVolume.L, UnitVolume.ML], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_volume.UnitVolume:94394491895888', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'volume': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Volume', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'volume', 'schema': {'expected': ['volume'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionVolume', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Volume, required=True), 'type': FieldInfo(annotation=Literal['volume'], required=False, default='volume')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eee14550,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eec9caa0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "output_unit": SerField {                                                     key_py: Py(                                                         0x00007f1ebebb86b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055d9ee288050,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "volume": SerField {                                                     key_py: Py(                                                         0x00007f1ec2f06e78,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Volume",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ec2f06e78,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "volume",                                             },                                             expected_py: None,                                             name: "literal['volume']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionVolume",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionVolume", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebdda2730,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebdda2700,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "output_unit",                                                 lookup_key: Simple {                                                     key: "output_unit",                                                     py_key: Py(                                                         0x00007f1ebdde7270,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "output_unit",                                                                 Py(                                                                     0x00007f1ebdde7230,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ebebb86b0,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055d9ee288050,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "usgal": 6,                                                                     "ft3": 1,                                                                     "yd3": 4,                                                                     "usfloz": 5,                                                                     "l": 7,                                                                     "cm3": 0,                                                                     "m3": 3,                                                                     "ml": 8,                                                                     "in3": 2,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007f1ebdde71c0,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007f1ebe5f1bb0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1c10,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1c70,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1cd0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1d30,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1d90,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1df0,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1e50,                                                                 ),                                                                 Py(                                                                     0x00007f1ebe5f1eb0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'cm3', 'ft3', 'in3', 'm3', 'yd3', 'usfloz', 'usgal', 'l' or 'ml'",                                                         strict: false,                                                         class_repr: "UnitVolume",                                                         name: "str-enum[UnitVolume]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "volume",                                                 lookup_key: Simple {                                                     key: "volume",                                                     py_key: Py(                                                         0x00007f1ebdda2760,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "volume",                                                                 Py(                                                                     0x00007f1ebdda2670,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec2f06e78,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Volume",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eec9caa0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "Volume",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebdda25b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebdda26a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ec2f06e78,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "volume": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdde72c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ec2f06e78,                                                 ),                                             ],                                         },                                         expected_repr: "'volume'",                                         name: "literal['volume']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['volume']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionVolume",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eee14550,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionVolume",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.volume.Volume, type: Literal['volume'] = 'volume') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: Volume

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=Volume, required=True), 'type': FieldInfo(annotation=Literal['volume'], required=False, default='volume')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['volume']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.ok_modeling_cmd_response.OptionZoomToFit(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'data': <class 'kittycad.models.zoom_to_fit.ZoomToFit'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'type': typing.Literal['zoom_to_fit']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

__firstlineno__ = 869

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[InvalidSchema, AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.ok_modeling_cmd_response'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94394486511008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.ok_modeling_cmd_response.OptionZoomToFit'>, 'config': {'title': 'OptionZoomToFit'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.OptionZoomToFit'>>]}, 'ref': 'kittycad.models.ok_modeling_cmd_response.OptionZoomToFit:94394503447248', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.zoom_to_fit.ZoomToFit'>, 'config': {'title': 'ZoomToFit'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.zoom_to_fit.ZoomToFit'>>]}, 'ref': 'kittycad.models.zoom_to_fit.ZoomToFit:94394502483088', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'settings': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.camera_settings.CameraSettings'>, 'config': {'title': 'CameraSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.camera_settings.CameraSettings'>>]}, 'ref': 'kittycad.models.camera_settings.CameraSettings:94394493063664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'orientation': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point4d.Point4d'>, 'config': {'title': 'Point4d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point4d.Point4d'>>]}, 'ref': 'kittycad.models.point4d.Point4d:94394493230224', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'w': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point4d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'ortho': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'ortho_scale': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'pos': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94394486511008', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'CameraSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'ZoomToFit', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'zoom_to_fit', 'schema': {'expected': ['zoom_to_fit'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionZoomToFit', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields__: ClassVar[Dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ZoomToFit, required=True), 'type': FieldInfo(annotation=Literal['zoom_to_fit'], required=False, default='zoom_to_fit')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055d9eed8c2d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "data": SerField {                         key_py: Py(                             0x00007f1ec2f01ed0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055d9eeca0c90,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "settings": SerField {                                                     key_py: Py(                                                         0x00007f1ec1e4c8b0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Model(                                                             ModelSerializer {                                                                 class: Py(                                                                     0x000055d9ee3a51f0,                                                                 ),                                                                 serializer: Fields(                                                                     GeneralFieldsSerializer {                                                                         fields: {                                                                             "up": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec0d2eeb0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddff30,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "ortho_scale": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe3580f0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "orientation": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebe358070,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Model(                                                                                         ModelSerializer {                                                                                             class: Py(                                                                                                 0x000055d9ee3cdc90,                                                                                             ),                                                                                             serializer: Fields(                                                                                                 GeneralFieldsSerializer {                                                                                                     fields: {                                                                                                         "x": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08838,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "y": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08868,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "w": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08808,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                         "z": SerField {                                                                                                             key_py: Py(                                                                                                                 0x00007f1ec2f08898,                                                                                                             ),                                                                                                             alias: None,                                                                                                             alias_py: None,                                                                                                             serializer: Some(                                                                                                                 Float(                                                                                                                     FloatSerializer {                                                                                                                         inf_nan_mode: Null,                                                                                                                     },                                                                                                                 ),                                                                                                             ),                                                                                                             required: true,                                                                                                         },                                                                                                     },                                                                                                     computed_fields: Some(                                                                                                         ComputedFields(                                                                                                             [],                                                                                                         ),                                                                                                     ),                                                                                                     mode: SimpleDict,                                                                                                     extra_serializer: None,                                                                                                     filter: SchemaFilter {                                                                                                         include: None,                                                                                                         exclude: None,                                                                                                     },                                                                                                     required_fields: 4,                                                                                                 },                                                                                             ),                                                                                             has_extra: false,                                                                                             root_model: false,                                                                                             name: "Point4d",                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "pos": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2f05408,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "fov_y": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ebeddfde0,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     WithDefault(                                                                                         WithDefaultSerializer {                                                                                             default: Default(                                                                                                 Py(                                                                                                     0x00007f1ec2ed0400,                                                                                                 ),                                                                                             ),                                                                                             serializer: Nullable(                                                                                                 NullableSerializer {                                                                                                     serializer: Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                             "center": SerField {                                                                                 key_py: Py(                                                                                     0x00007f1ec2820180,                                                                                 ),                                                                                 alias: None,                                                                                 alias_py: None,                                                                                 serializer: Some(                                                                                     Recursive(                                                                                         DefinitionRefSerializer {                                                                                             definition: "...",                                                                                             retry_with_lax_check: true,                                                                                         },                                                                                     ),                                                                                 ),                                                                                 required: true,                                                                             },                                                                         },                                                                         computed_fields: Some(                                                                             ComputedFields(                                                                                 [],                                                                             ),                                                                         ),                                                                         mode: SimpleDict,                                                                         extra_serializer: None,                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         required_fields: 7,                                                                     },                                                                 ),                                                                 has_extra: false,                                                                 root_model: false,                                                                 name: "CameraSettings",                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 1,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "ZoomToFit",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007f1ec2f06bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007f1ebed87bb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "zoom_to_fit",                                             },                                             expected_py: None,                                             name: "literal['zoom_to_fit']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionZoomToFit",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55d9edd655a0), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7f1ec2f08898), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7f1ec2f08868), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7f1ec2f08838), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionZoomToFit", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "data",                         lookup_key: Simple {                             key: "data",                             py_key: Py(                                 0x00007f1ebded7a20,                             ),                             path: LookupPath(                                 [                                     S(                                         "data",                                         Py(                                             0x00007f1ebded7ae0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f01ed0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "settings",                                                 lookup_key: Simple {                                                     key: "settings",                                                     py_key: Py(                                                         0x00007f1ebdd5a9f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "settings",                                                                 Py(                                                                     0x00007f1ebdd59a70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007f1ec1e4c8b0,                                                 ),                                                 validator: Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007f1ebded74b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007f1ebded7600,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2820180,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "fov_y",                                                                         lookup_key: Simple {                                                                             key: "fov_y",                                                                             py_key: Py(                                                                                 0x00007f1ebded7480,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "fov_y",                                                                                         Py(                                                                                             0x00007f1ebded74e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddfde0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "orientation",                                                                         lookup_key: Simple {                                                                             key: "orientation",                                                                             py_key: Py(                                                                                 0x00007f1ebdee78b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "orientation",                                                                                         Py(                                                                                             0x00007f1ebdee71f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe358070,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "w",                                                                                                 lookup_key: Simple {                                                                                                     key: "w",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08808,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "w",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08808,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08808,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08838,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08838,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08838,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08868,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08868,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08868,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "z",                                                                                                 lookup_key: Simple {                                                                                                     key: "z",                                                                                                     py_key: Py(                                                                                                         0x00007f1ec2f08898,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "z",                                                                                                                 Py(                                                                                                                     0x00007f1ec2f08898,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007f1ec2f08898,                                                                                                 ),                                                                                                 validator: Float(                                                                                                     FloatValidator {                                                                                                         strict: false,                                                                                                         allow_inf_nan: true,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point4d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055d9ee3cdc90,                                                                                 ),                                                                                 generic_origin: None,                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                                 name: "Point4d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho",                                                                         lookup_key: Simple {                                                                             key: "ortho",                                                                             py_key: Py(                                                                                 0x00007f1ebded7840,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho",                                                                                         Py(                                                                                             0x00007f1ebded77e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebeddff30,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "ortho_scale",                                                                         lookup_key: Simple {                                                                             key: "ortho_scale",                                                                             py_key: Py(                                                                                 0x00007f1ebdee5ff0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "ortho_scale",                                                                                         Py(                                                                                             0x00007f1ebdee7eb0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ebe3580f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007f1ec2ed0400,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         name: "nullable[float]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[float]]",                                                                                 undefined: Py(                                                                                     0x00007f1ec0cae3d0,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "pos",                                                                         lookup_key: Simple {                                                                             key: "pos",                                                                             py_key: Py(                                                                                 0x00007f1ebded7810,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "pos",                                                                                         Py(                                                                                             0x00007f1ebded7ab0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec2f05408,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "up",                                                                         lookup_key: Simple {                                                                             key: "up",                                                                             py_key: Py(                                                                                 0x00007f1ebded7960,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "up",                                                                                         Py(                                                                                             0x00007f1ebded7a50,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007f1ec0d2eeb0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "CameraSettings",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055d9ee3a51f0,                                                         ),                                                         generic_origin: None,                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007f1ec0cae3d0,                                                         ),                                                         name: "CameraSettings",                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "ZoomToFit",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055d9eeca0c90,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                                 name: "ZoomToFit",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007f1ebded79c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007f1ebded7b10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007f1ec2f06bf0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007f1ebed87bb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "zoom_to_fit": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007f1ebdd5aa80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007f1ebed87bb0,                                                 ),                                             ],                                         },                                         expected_repr: "'zoom_to_fit'",                                         name: "literal['zoom_to_fit']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['zoom_to_fit']]",                                 undefined: Py(                                     0x00007f1ec0cae3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionZoomToFit",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055d9eed8c2d0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007f1ec0cae3d0,         ),         name: "OptionZoomToFit",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7f1ec2f08838), path: LookupPath([S("x", Py(0x7f1ec2f08838))]) }, name_py: Py(0x7f1ec2f08838), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7f1ec2f08868), path: LookupPath([S("y", Py(0x7f1ec2f08868))]) }, name_py: Py(0x7f1ec2f08868), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7f1ec2f08898), path: LookupPath([S("z", Py(0x7f1ec2f08898))]) }, name_py: Py(0x7f1ec2f08898), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55d9edd655a0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7f1ec0cae3d0), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__replace__(**changes)

Return type:

Self

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_recursion__(object)

Returns the string representation of a recursive object.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, data: kittycad.models.zoom_to_fit.ZoomToFit, type: Literal['zoom_to_fit'] = 'zoom_to_fit') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__static_attributes__ = ()

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

data: ZoomToFit

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[dict[str, FieldInfo]] = {'data': FieldInfo(annotation=ZoomToFit, required=True), 'type': FieldInfo(annotation=Literal['zoom_to_fit'], required=False, default='zoom_to_fit')}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (Optional[Mapping[str, Any]]) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['zoom_to_fit']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self