kittycad.models.ok_web_socket_response_data

Classes

ExportData(**data)

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

IceServerInfoData(**data)

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

MetricsRequestData(**data)

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

ModelingData(**data)

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

SdpAnswerData(**data)

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

TrickleIceData(**data)

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

export(**data)

The exported files.

ice_server_info(**data)

Information about the ICE servers.

metrics_request(**data)

Request a collection of metrics, to include WebRTC.

modeling(**data)

The modeling command response.

sdp_answer(**data)

The SDP answer response.

trickle_ice(**data)

The trickle ICE candidate response.

class kittycad.models.ok_web_socket_response_data.ExportData(**data)[source][source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__abstractmethods__ = frozenset({})[source]
__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__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]', '__signature__': 'ClassVar[Signature]', 'files': typing.List[kittycad.models.raw_file.RawFile], 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]'}[source]
classmethod __class_getitem__(typevar_values)[source]
__class_vars__: ClassVar[set[str]] = {}[source]
__copy__()[source]

Returns a shallow copy of the model.

Return type:

Model

__deepcopy__(memo=None)[source]

Returns a deep copy of the model.

Return type:

Model

__delattr__(item)[source]

Implement delattr(self, name).

Return type:

Any

__dict__[source]
__eq__(other)[source]

Return self==value.

Return type:

bool

__fields__ = {'files': FieldInfo(annotation=List[kittycad.models.raw_file.RawFile], required=True)}[source]
property __fields_set__: set[str][source]
classmethod __get_pydantic_core_schema__(_BaseModel__source, _BaseModel__handler)[source]

Hook into generating the model’s CoreSchema.

Parameters:
  • __source – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

  • __handler – Call into Pydantic’s internal JSON schema generation. A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TuplePositionalSchema, TupleVariableSchema, 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]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(_BaseModel__core_schema, _BaseModel__handler)[source]

Hook into generating the model’s JSON schema.

Parameters:
  • __core_schema – 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 – 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)[source]
Return type:

Any

__getstate__()[source]
Return type:

dict[Any, Any]

__hash__ = None[source]
__init__(**data)[source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__iter__()[source]

So dict(model) works.

Return type:

TupleGenerator

__module__ = 'kittycad.models.ok_web_socket_response_data'[source]
__pretty__(fmt, **kwargs)[source]

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

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[dict[str, ModelPrivateAttr]] = {}[source]
__pydantic_complete__: ClassVar[bool] = True[source]
__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_web_socket_response_data.ExportData'>, 'config': {'title': 'ExportData'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_web_socket_response_data.ExportData'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_web_socket_response_data.ExportData'>>]}, 'ref': 'kittycad.models.ok_web_socket_response_data.ExportData:93825023742176', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'files': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.raw_file.RawFile'>, 'config': {'title': 'RawFile'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.raw_file.RawFile'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.raw_file.RawFile'>>]}, 'ref': 'kittycad.models.raw_file.RawFile:93825017753280', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'contents': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'bytes'}, 'type': 'model-field'}, 'name': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'RawFile', 'type': 'model-fields'}, 'type': 'model'}, 'strict': False, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'ExportData', 'type': 'model-fields'}, 'type': 'model'}[source]
__pydantic_custom_init__: ClassVar[bool] = False[source]
__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})[source]
__pydantic_extra__: dict[str, Any] | None[source]
__pydantic_fields_set__: set[str][source]
__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}[source]
classmethod __pydantic_init_subclass__(**kwargs)[source]

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] = {'Annotated': <pydantic._internal._model_construction._PydanticWeakRef object>, 'BaseModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Field': <pydantic._internal._model_construction._PydanticWeakRef object>, 'IceServer': <pydantic._internal._model_construction._PydanticWeakRef object>, 'IceServerInfoData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'List': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Literal': <pydantic._internal._model_construction._PydanticWeakRef object>, 'ModelingData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'OkModelingCmdResponse': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RawFile': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RootModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcIceCandidateInit': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcSessionDescription': <pydantic._internal._model_construction._PydanticWeakRef object>, 'SdpAnswerData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'TrickleIceData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Union': <pydantic._internal._model_construction._PydanticWeakRef object>, '__builtins__': {'ArithmeticError': <class 'ArithmeticError'>, 'AssertionError': <class 'AssertionError'>, 'AttributeError': <class 'AttributeError'>, 'BaseException': <class 'BaseException'>, 'BlockingIOError': <class 'BlockingIOError'>, 'BrokenPipeError': <class 'BrokenPipeError'>, 'BufferError': <class 'BufferError'>, 'BytesWarning': <class 'BytesWarning'>, 'ChildProcessError': <class 'ChildProcessError'>, 'ConnectionAbortedError': <class 'ConnectionAbortedError'>, 'ConnectionError': <class 'ConnectionError'>, 'ConnectionRefusedError': <class 'ConnectionRefusedError'>, 'ConnectionResetError': <class 'ConnectionResetError'>, 'DeprecationWarning': <class 'DeprecationWarning'>, 'EOFError': <class 'EOFError'>, 'Ellipsis': Ellipsis, 'EnvironmentError': <class 'OSError'>, 'Exception': <class 'Exception'>, 'False': False, 'FileExistsError': <class 'FileExistsError'>, 'FileNotFoundError': <class 'FileNotFoundError'>, 'FloatingPointError': <class 'FloatingPointError'>, 'FutureWarning': <class 'FutureWarning'>, 'GeneratorExit': <class 'GeneratorExit'>, 'IOError': <class 'OSError'>, 'ImportError': <class 'ImportError'>, 'ImportWarning': <class 'ImportWarning'>, 'IndentationError': <class 'IndentationError'>, 'IndexError': <class 'IndexError'>, 'InterruptedError': <class 'InterruptedError'>, 'IsADirectoryError': <class 'IsADirectoryError'>, 'KeyError': <class 'KeyError'>, 'KeyboardInterrupt': <class 'KeyboardInterrupt'>, 'LookupError': <class 'LookupError'>, 'MemoryError': <class 'MemoryError'>, 'ModuleNotFoundError': <class 'ModuleNotFoundError'>, 'NameError': <class 'NameError'>, 'None': None, 'NotADirectoryError': <class 'NotADirectoryError'>, 'NotImplemented': NotImplemented, 'NotImplementedError': <class 'NotImplementedError'>, 'OSError': <class 'OSError'>, 'OverflowError': <class 'OverflowError'>, 'PendingDeprecationWarning': <class 'PendingDeprecationWarning'>, 'PermissionError': <class 'PermissionError'>, 'ProcessLookupError': <class 'ProcessLookupError'>, 'RecursionError': <class 'RecursionError'>, 'ReferenceError': <class 'ReferenceError'>, 'ResourceWarning': <class 'ResourceWarning'>, 'RuntimeError': <class 'RuntimeError'>, 'RuntimeWarning': <class 'RuntimeWarning'>, 'StopAsyncIteration': <class 'StopAsyncIteration'>, 'StopIteration': <class 'StopIteration'>, 'SyntaxError': <class 'SyntaxError'>, 'SyntaxWarning': <class 'SyntaxWarning'>, 'SystemError': <class 'SystemError'>, 'SystemExit': <class 'SystemExit'>, 'TabError': <class 'TabError'>, 'TimeoutError': <class 'TimeoutError'>, 'True': True, 'TypeError': <class 'TypeError'>, 'UnboundLocalError': <class 'UnboundLocalError'>, 'UnicodeDecodeError': <class 'UnicodeDecodeError'>, 'UnicodeEncodeError': <class 'UnicodeEncodeError'>, 'UnicodeError': <class 'UnicodeError'>, 'UnicodeTranslateError': <class 'UnicodeTranslateError'>, 'UnicodeWarning': <class 'UnicodeWarning'>, 'UserWarning': <class 'UserWarning'>, 'ValueError': <class 'ValueError'>, 'Warning': <class 'Warning'>, 'ZeroDivisionError': <class 'ZeroDivisionError'>, '__build_class__': <built-in function __build_class__>, '__debug__': True, '__doc__': "Built-in functions, exceptions, and other objects.\n\nNoteworthy: None is the `nil' object; Ellipsis represents `...' in slices.", '__import__': <built-in function __import__>, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__name__': 'builtins', '__package__': '', '__spec__': ModuleSpec(name='builtins', loader=<class '_frozen_importlib.BuiltinImporter'>, origin='built-in'), 'abs': <built-in function abs>, 'all': <built-in function all>, 'any': <built-in function any>, 'ascii': <built-in function ascii>, 'bin': <built-in function bin>, 'bool': <class 'bool'>, 'breakpoint': <built-in function breakpoint>, 'bytearray': <class 'bytearray'>, 'bytes': <class 'bytes'>, 'callable': <built-in function callable>, 'chr': <built-in function chr>, 'classmethod': <class 'classmethod'>, 'compile': <built-in function compile>, 'complex': <class 'complex'>, 'copyright': Copyright (c) 2001-2023 Python Software Foundation. All Rights Reserved.  Copyright (c) 2000 BeOpen.com. All Rights Reserved.  Copyright (c) 1995-2001 Corporation for National Research Initiatives. All Rights Reserved.  Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam. All Rights Reserved., 'credits':     Thanks to CWI, CNRI, BeOpen.com, Zope Corporation and a cast of thousands     for supporting Python development.  See www.python.org for more information., 'delattr': <built-in function delattr>, 'dict': <class 'dict'>, 'dir': <built-in function dir>, 'divmod': <built-in function divmod>, 'enumerate': <class 'enumerate'>, 'eval': <built-in function eval>, 'exec': <built-in function exec>, 'exit': Use exit() or Ctrl-D (i.e. EOF) to exit, 'filter': <class 'filter'>, 'float': <class 'float'>, 'format': <built-in function format>, 'frozenset': <class 'frozenset'>, 'getattr': <built-in function getattr>, 'globals': <built-in function globals>, 'hasattr': <built-in function hasattr>, 'hash': <built-in function hash>, 'help': Type help() for interactive help, or help(object) for help about object., 'hex': <built-in function hex>, 'id': <built-in function id>, 'input': <built-in function input>, 'int': <class 'int'>, 'isinstance': <built-in function isinstance>, 'issubclass': <built-in function issubclass>, 'iter': <built-in function iter>, 'len': <built-in function len>, 'license': Type license() to see the full license text, 'list': <class 'list'>, 'locals': <built-in function locals>, 'map': <class 'map'>, 'max': <built-in function max>, 'memoryview': <class 'memoryview'>, 'min': <built-in function min>, 'next': <built-in function next>, 'object': <class 'object'>, 'oct': <built-in function oct>, 'open': <built-in function open>, 'ord': <built-in function ord>, 'pow': <built-in function pow>, 'print': <built-in function print>, 'property': <class 'property'>, 'quit': Use quit() or Ctrl-D (i.e. EOF) to exit, 'range': <class 'range'>, 'repr': <built-in function repr>, 'reversed': <class 'reversed'>, 'round': <built-in function round>, 'set': <class 'set'>, 'setattr': <built-in function setattr>, 'slice': <class 'slice'>, 'sorted': <built-in function sorted>, 'staticmethod': <class 'staticmethod'>, 'str': <class 'str'>, 'sum': <built-in function sum>, 'super': <class 'super'>, 'tuple': <class 'tuple'>, 'type': <class 'type'>, 'vars': <built-in function vars>, 'zip': <class 'zip'>}, '__cached__': '/home/user/src/kittycad/models/__pycache__/ok_web_socket_response_data.cpython-39.pyc', '__doc__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__file__': '/home/user/src/kittycad/models/ok_web_socket_response_data.py', '__loader__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__name__': 'kittycad.models.ok_web_socket_response_data', '__package__': 'kittycad.models', '__spec__': <pydantic._internal._model_construction._PydanticWeakRef object>, 'ice_server_info': <pydantic._internal._model_construction._PydanticWeakRef object>, 'modeling': <pydantic._internal._model_construction._PydanticWeakRef object>, 'sdp_answer': <pydantic._internal._model_construction._PydanticWeakRef object>, 'trickle_ice': <pydantic._internal._model_construction._PydanticWeakRef object>}[source]
__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None[source]
__pydantic_private__: dict[str, Any] | None[source]
__pydantic_root_model__: ClassVar[bool] = False[source]
__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x00005555573610e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "files": SerField {                         key_py: Py(                             0x00007fffff8c9930,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Model(                                         ModelSerializer {                                             class: Py(                                                 0x0000555556daaec0,                                             ),                                             serializer: Fields(                                                 GeneralFieldsSerializer {                                                     fields: {                                                         "contents": SerField {                                                             key_py: Py(                                                                 0x00007fffff89d8f0,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 Bytes(                                                                     BytesSerializer,                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "name": SerField {                                                             key_py: Py(                                                                 0x00007fffff9521b0,                                                             ),                                                             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: "RawFile",                                         },                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[RawFile]",                                 },                             ),                         ),                         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: "ExportData",     }, ), definitions=[])[source]
__pydantic_validator__: ClassVar[SchemaValidator] = SchemaValidator(title="ExportData", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "files",                         lookup_key: Simple {                             key: "files",                             py_key: Py(                                 0x00007fffff8c9930,                             ),                             path: LookupPath(                                 [                                     S(                                         "files",                                         Py(                                             0x00007fffff8c9930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fffff8c9930,                         ),                         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(                                                                     0x00007fffff89d8f0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "contents",                                                                             Py(                                                                                 0x00007fffff89d8f0,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fffff89d8f0,                                                             ),                                                             validator: Bytes(                                                                 BytesValidator {                                                                     strict: false,                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "name",                                                             lookup_key: Simple {                                                                 key: "name",                                                                 py_key: Py(                                                                     0x00007fffff9521b0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "name",                                                                             Py(                                                                                 0x00007fffff9521b0,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fffff9521b0,                                                             ),                                                             validator: Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                     ],                                                     model_name: "RawFile",                                                     extra_behavior: Ignore,                                                     extras_validator: None,                                                     strict: false,                                                     from_attributes: false,                                                     loc_by_alias: true,                                                 },                                             ),                                             class: Py(                                                 0x0000555556daaec0,                                             ),                                             post_init: None,                                             frozen: false,                                             custom_init: false,                                             root_model: false,                                             name: "RawFile",                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "ExportData",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x00005555573610e0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         name: "ExportData",     }, ), definitions=[])[source]
__repr__()[source]

Return repr(self).

Return type:

str

__repr_args__()[source]
__repr_name__()[source]

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

Return type:

str

__repr_str__(join_str)[source]
Return type:

str

__rich_repr__()[source]

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

__setattr__(name, value)[source]

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)[source]
Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, files: List[kittycad.models.raw_file.RawFile]) -> None>[source]
__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')[source]
__str__()[source]

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>[source]
_calculate_keys(*args, **kwargs)[source]
Return type:

Any

_check_frozen(name, value)[source]
Return type:

None

_copy_and_set_values(*args, **kwargs)[source]
Return type:

Any

classmethod _get_value(cls, *args, **kwargs)[source]
Return type:

Any

_iter(*args, **kwargs)[source]
Return type:

Any

classmethod construct(cls, _fields_set=None, **values)[source]
Return type:

Model

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

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:
  • include (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to include in the copied model.

  • exclude (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to exclude in the copied model.

  • update (Dict[str, Any] | None) – Optional dictionary of field-value pairs to override field values in the copied model.

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

Return type:

Model

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)[source]
Return type:

Dict[str, Any]

files: List[RawFile][source]
classmethod from_orm(cls, obj)[source]
Return type:

Model

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)[source]
Return type:

str

property model_computed_fields: dict[str, ComputedFieldInfo][source]

Get the computed fields of this model instance.

Returns:

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}[source]

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

classmethod model_construct(_fields_set=None, **values)[source]

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. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Parameters:
  • _fields_set (set[str] | None) – The set of field names accepted for the Model instance.

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

Return type:

Model

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:
  • update (dict[str, Any] | None) – 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:

Model

Returns:

New model instance.

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

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump

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

Parameters:
  • mode – The mode in which to_python should run. If mode is ‘json’, the dictionary will only contain JSON serializable types. If mode is ‘python’, the dictionary may contain any Python objects.

  • include – A list of fields to include in the output.

  • exclude – A list of fields to exclude from the output.

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

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

  • exclude_defaults – Whether to exclude fields that are set to their default value from the output.

  • exclude_none – Whether to exclude fields that have a value of None from the output.

  • round_trip – Whether to enable serialization and deserialization round-trip support.

  • warnings – Whether to log warnings when invalid fields are encountered.

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump_json

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

Parameters:
  • indent – Indentation to use in the JSON output. If None is passed, the output will be compact.

  • include – Field(s) to include in the JSON output. Can take either a string or set of strings.

  • exclude – Field(s) to exclude from the JSON output. Can take either a string or set of strings.

  • by_alias – Whether to serialize using field aliases.

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

  • exclude_defaults – Whether to exclude fields that have the default value.

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

  • round_trip – Whether to use serialization/deserialization between JSON and class instance.

  • warnings – Whether to show any warnings that occurred during serialization.

Returns:

A JSON string representation of the model.

property model_extra[source]

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]] = {'files': FieldInfo(annotation=List[kittycad.models.raw_file.RawFile], required=True)}[source]

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str][source]

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')[source]

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)[source]

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)[source]

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)[source]

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 – Whether to force the rebuilding of the model schema, defaults to False.

  • raise_errors – Whether to raise errors, defaults to True.

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

  • _types_namespace – The types namespace, defaults to 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)[source]

Validate a pydantic model instance.

Parameters:
  • obj (Any) – The object to validate.

  • strict (bool | None) – Whether to raise an exception on invalid fields.

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

  • context (dict[str, Any] | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Model

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)[source]

Usage docs: https://docs.pydantic.dev/2.5/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 (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

Raises:

ValueError – If json_data is not a JSON string.

classmethod model_validate_strings(obj, *, strict=None, context=None)[source]

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

Parameters:
  • obj (Any) – The object contains string data to validate.

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

  • context (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

classmethod parse_file(cls, path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod parse_obj(cls, obj)[source]
Return type:

Model

classmethod parse_raw(cls, b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod schema(cls, by_alias=True, ref_template='#/$defs/{model}')[source]
Return type:

Dict[str, Any]

classmethod schema_json(cls, *, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)[source]
Return type:

str

classmethod update_forward_refs(cls, **localns)[source]
Return type:

None

classmethod validate(cls, value)[source]
Return type:

Model

class kittycad.models.ok_web_socket_response_data.IceServerInfoData(**data)[source][source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__abstractmethods__ = frozenset({})[source]
__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__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]', '__signature__': 'ClassVar[Signature]', 'ice_servers': typing.List[kittycad.models.ice_server.IceServer], 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]'}[source]
classmethod __class_getitem__(typevar_values)[source]
__class_vars__: ClassVar[set[str]] = {}[source]
__copy__()[source]

Returns a shallow copy of the model.

Return type:

Model

__deepcopy__(memo=None)[source]

Returns a deep copy of the model.

Return type:

Model

__delattr__(item)[source]

Implement delattr(self, name).

Return type:

Any

__dict__[source]
__eq__(other)[source]

Return self==value.

Return type:

bool

__fields__ = {'ice_servers': FieldInfo(annotation=List[kittycad.models.ice_server.IceServer], required=True)}[source]
property __fields_set__: set[str][source]
classmethod __get_pydantic_core_schema__(_BaseModel__source, _BaseModel__handler)[source]

Hook into generating the model’s CoreSchema.

Parameters:
  • __source – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

  • __handler – Call into Pydantic’s internal JSON schema generation. A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TuplePositionalSchema, TupleVariableSchema, 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]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(_BaseModel__core_schema, _BaseModel__handler)[source]

Hook into generating the model’s JSON schema.

Parameters:
  • __core_schema – 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 – 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)[source]
Return type:

Any

__getstate__()[source]
Return type:

dict[Any, Any]

__hash__ = None[source]
__init__(**data)[source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__iter__()[source]

So dict(model) works.

Return type:

TupleGenerator

__module__ = 'kittycad.models.ok_web_socket_response_data'[source]
__pretty__(fmt, **kwargs)[source]

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

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[dict[str, ModelPrivateAttr]] = {}[source]
__pydantic_complete__: ClassVar[bool] = True[source]
__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_web_socket_response_data.IceServerInfoData'>, 'config': {'title': 'IceServerInfoData'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_web_socket_response_data.IceServerInfoData'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_web_socket_response_data.IceServerInfoData'>>]}, 'ref': 'kittycad.models.ok_web_socket_response_data.IceServerInfoData:93825023343840', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'ice_servers': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.ice_server.IceServer'>, 'config': {'title': 'IceServer'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ice_server.IceServer'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ice_server.IceServer'>>]}, 'ref': 'kittycad.models.ice_server.IceServer:93825018058384', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'credential': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'urls': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'str'}, 'strict': False, 'type': 'list'}, 'type': 'model-field'}, 'username': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'schema': {'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'IceServer', 'type': 'model-fields'}, 'type': 'model'}, 'strict': False, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'IceServerInfoData', 'type': 'model-fields'}, 'type': 'model'}[source]
__pydantic_custom_init__: ClassVar[bool] = False[source]
__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})[source]
__pydantic_extra__: dict[str, Any] | None[source]
__pydantic_fields_set__: set[str][source]
__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}[source]
classmethod __pydantic_init_subclass__(**kwargs)[source]

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] = {'Annotated': <pydantic._internal._model_construction._PydanticWeakRef object>, 'BaseModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Field': <pydantic._internal._model_construction._PydanticWeakRef object>, 'IceServer': <pydantic._internal._model_construction._PydanticWeakRef object>, 'List': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Literal': <pydantic._internal._model_construction._PydanticWeakRef object>, 'OkModelingCmdResponse': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RawFile': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RootModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcIceCandidateInit': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcSessionDescription': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Union': <pydantic._internal._model_construction._PydanticWeakRef object>, '__builtins__': {'ArithmeticError': <class 'ArithmeticError'>, 'AssertionError': <class 'AssertionError'>, 'AttributeError': <class 'AttributeError'>, 'BaseException': <class 'BaseException'>, 'BlockingIOError': <class 'BlockingIOError'>, 'BrokenPipeError': <class 'BrokenPipeError'>, 'BufferError': <class 'BufferError'>, 'BytesWarning': <class 'BytesWarning'>, 'ChildProcessError': <class 'ChildProcessError'>, 'ConnectionAbortedError': <class 'ConnectionAbortedError'>, 'ConnectionError': <class 'ConnectionError'>, 'ConnectionRefusedError': <class 'ConnectionRefusedError'>, 'ConnectionResetError': <class 'ConnectionResetError'>, 'DeprecationWarning': <class 'DeprecationWarning'>, 'EOFError': <class 'EOFError'>, 'Ellipsis': Ellipsis, 'EnvironmentError': <class 'OSError'>, 'Exception': <class 'Exception'>, 'False': False, 'FileExistsError': <class 'FileExistsError'>, 'FileNotFoundError': <class 'FileNotFoundError'>, 'FloatingPointError': <class 'FloatingPointError'>, 'FutureWarning': <class 'FutureWarning'>, 'GeneratorExit': <class 'GeneratorExit'>, 'IOError': <class 'OSError'>, 'ImportError': <class 'ImportError'>, 'ImportWarning': <class 'ImportWarning'>, 'IndentationError': <class 'IndentationError'>, 'IndexError': <class 'IndexError'>, 'InterruptedError': <class 'InterruptedError'>, 'IsADirectoryError': <class 'IsADirectoryError'>, 'KeyError': <class 'KeyError'>, 'KeyboardInterrupt': <class 'KeyboardInterrupt'>, 'LookupError': <class 'LookupError'>, 'MemoryError': <class 'MemoryError'>, 'ModuleNotFoundError': <class 'ModuleNotFoundError'>, 'NameError': <class 'NameError'>, 'None': None, 'NotADirectoryError': <class 'NotADirectoryError'>, 'NotImplemented': NotImplemented, 'NotImplementedError': <class 'NotImplementedError'>, 'OSError': <class 'OSError'>, 'OverflowError': <class 'OverflowError'>, 'PendingDeprecationWarning': <class 'PendingDeprecationWarning'>, 'PermissionError': <class 'PermissionError'>, 'ProcessLookupError': <class 'ProcessLookupError'>, 'RecursionError': <class 'RecursionError'>, 'ReferenceError': <class 'ReferenceError'>, 'ResourceWarning': <class 'ResourceWarning'>, 'RuntimeError': <class 'RuntimeError'>, 'RuntimeWarning': <class 'RuntimeWarning'>, 'StopAsyncIteration': <class 'StopAsyncIteration'>, 'StopIteration': <class 'StopIteration'>, 'SyntaxError': <class 'SyntaxError'>, 'SyntaxWarning': <class 'SyntaxWarning'>, 'SystemError': <class 'SystemError'>, 'SystemExit': <class 'SystemExit'>, 'TabError': <class 'TabError'>, 'TimeoutError': <class 'TimeoutError'>, 'True': True, 'TypeError': <class 'TypeError'>, 'UnboundLocalError': <class 'UnboundLocalError'>, 'UnicodeDecodeError': <class 'UnicodeDecodeError'>, 'UnicodeEncodeError': <class 'UnicodeEncodeError'>, 'UnicodeError': <class 'UnicodeError'>, 'UnicodeTranslateError': <class 'UnicodeTranslateError'>, 'UnicodeWarning': <class 'UnicodeWarning'>, 'UserWarning': <class 'UserWarning'>, 'ValueError': <class 'ValueError'>, 'Warning': <class 'Warning'>, 'ZeroDivisionError': <class 'ZeroDivisionError'>, '__build_class__': <built-in function __build_class__>, '__debug__': True, '__doc__': "Built-in functions, exceptions, and other objects.\n\nNoteworthy: None is the `nil' object; Ellipsis represents `...' in slices.", '__import__': <built-in function __import__>, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__name__': 'builtins', '__package__': '', '__spec__': ModuleSpec(name='builtins', loader=<class '_frozen_importlib.BuiltinImporter'>, origin='built-in'), 'abs': <built-in function abs>, 'all': <built-in function all>, 'any': <built-in function any>, 'ascii': <built-in function ascii>, 'bin': <built-in function bin>, 'bool': <class 'bool'>, 'breakpoint': <built-in function breakpoint>, 'bytearray': <class 'bytearray'>, 'bytes': <class 'bytes'>, 'callable': <built-in function callable>, 'chr': <built-in function chr>, 'classmethod': <class 'classmethod'>, 'compile': <built-in function compile>, 'complex': <class 'complex'>, 'copyright': Copyright (c) 2001-2023 Python Software Foundation. All Rights Reserved.  Copyright (c) 2000 BeOpen.com. All Rights Reserved.  Copyright (c) 1995-2001 Corporation for National Research Initiatives. All Rights Reserved.  Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam. All Rights Reserved., 'credits':     Thanks to CWI, CNRI, BeOpen.com, Zope Corporation and a cast of thousands     for supporting Python development.  See www.python.org for more information., 'delattr': <built-in function delattr>, 'dict': <class 'dict'>, 'dir': <built-in function dir>, 'divmod': <built-in function divmod>, 'enumerate': <class 'enumerate'>, 'eval': <built-in function eval>, 'exec': <built-in function exec>, 'exit': Use exit() or Ctrl-D (i.e. EOF) to exit, 'filter': <class 'filter'>, 'float': <class 'float'>, 'format': <built-in function format>, 'frozenset': <class 'frozenset'>, 'getattr': <built-in function getattr>, 'globals': <built-in function globals>, 'hasattr': <built-in function hasattr>, 'hash': <built-in function hash>, 'help': Type help() for interactive help, or help(object) for help about object., 'hex': <built-in function hex>, 'id': <built-in function id>, 'input': <built-in function input>, 'int': <class 'int'>, 'isinstance': <built-in function isinstance>, 'issubclass': <built-in function issubclass>, 'iter': <built-in function iter>, 'len': <built-in function len>, 'license': Type license() to see the full license text, 'list': <class 'list'>, 'locals': <built-in function locals>, 'map': <class 'map'>, 'max': <built-in function max>, 'memoryview': <class 'memoryview'>, 'min': <built-in function min>, 'next': <built-in function next>, 'object': <class 'object'>, 'oct': <built-in function oct>, 'open': <built-in function open>, 'ord': <built-in function ord>, 'pow': <built-in function pow>, 'print': <built-in function print>, 'property': <class 'property'>, 'quit': Use quit() or Ctrl-D (i.e. EOF) to exit, 'range': <class 'range'>, 'repr': <built-in function repr>, 'reversed': <class 'reversed'>, 'round': <built-in function round>, 'set': <class 'set'>, 'setattr': <built-in function setattr>, 'slice': <class 'slice'>, 'sorted': <built-in function sorted>, 'staticmethod': <class 'staticmethod'>, 'str': <class 'str'>, 'sum': <built-in function sum>, 'super': <class 'super'>, 'tuple': <class 'tuple'>, 'type': <class 'type'>, 'vars': <built-in function vars>, 'zip': <class 'zip'>}, '__cached__': '/home/user/src/kittycad/models/__pycache__/ok_web_socket_response_data.cpython-39.pyc', '__doc__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__file__': '/home/user/src/kittycad/models/ok_web_socket_response_data.py', '__loader__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__name__': 'kittycad.models.ok_web_socket_response_data', '__package__': 'kittycad.models', '__spec__': <pydantic._internal._model_construction._PydanticWeakRef object>}[source]
__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None[source]
__pydantic_private__: dict[str, Any] | None[source]
__pydantic_root_model__: ClassVar[bool] = False[source]
__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x00005555572ffce0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "ice_servers": SerField {                         key_py: Py(                             0x00007fffe11b79f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Model(                                         ModelSerializer {                                             class: Py(                                                 0x0000555556df5690,                                             ),                                             serializer: Fields(                                                 GeneralFieldsSerializer {                                                     fields: {                                                         "credential": SerField {                                                             key_py: Py(                                                                 0x00007fffe10bc630,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007ffffff85420,                                                                             ),                                                                         ),                                                                         serializer: Nullable(                                                                             NullableSerializer {                                                                                 serializer: Str(                                                                                     StrSerializer,                                                                                 ),                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "urls": SerField {                                                             key_py: Py(                                                                 0x00007ffffdc81530,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 List(                                                                     ListSerializer {                                                                         item_serializer: Str(                                                                             StrSerializer,                                                                         ),                                                                         filter: SchemaFilter {                                                                             include: None,                                                                             exclude: None,                                                                         },                                                                         name: "list[str]",                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "username": SerField {                                                             key_py: Py(                                                                 0x00007fffff0bad30,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007ffffff85420,                                                                             ),                                                                         ),                                                                         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: "IceServer",                                         },                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[IceServer]",                                 },                             ),                         ),                         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: "IceServerInfoData",     }, ), definitions=[])[source]
__pydantic_validator__: ClassVar[SchemaValidator] = SchemaValidator(title="IceServerInfoData", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "ice_servers",                         lookup_key: Simple {                             key: "ice_servers",                             py_key: Py(                                 0x00007fffe11b79f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "ice_servers",                                         Py(                                             0x00007fffe11b79f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fffe11b79f0,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Model(                                         ModelValidator {                                             revalidate: Never,                                             validator: ModelFields(                                                 ModelFieldsValidator {                                                     fields: [                                                         Field {                                                             name: "credential",                                                             lookup_key: Simple {                                                                 key: "credential",                                                                 py_key: Py(                                                                     0x00007fffe10bc630,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "credential",                                                                             Py(                                                                                 0x00007fffe10bc630,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fffe10bc630,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007ffffff85420,                                                                         ),                                                                     ),                                                                     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]]",                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "urls",                                                             lookup_key: Simple {                                                                 key: "urls",                                                                 py_key: Py(                                                                     0x00007ffffdc81530,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "urls",                                                                             Py(                                                                                 0x00007ffffdc81530,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007ffffdc81530,                                                             ),                                                             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>,                                                                     ),                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "username",                                                             lookup_key: Simple {                                                                 key: "username",                                                                 py_key: Py(                                                                     0x00007fffff0bad30,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "username",                                                                             Py(                                                                                 0x00007fffff0bad30,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fffff0bad30,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007ffffff85420,                                                                         ),                                                                     ),                                                                     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]]",                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                     ],                                                     model_name: "IceServer",                                                     extra_behavior: Ignore,                                                     extras_validator: None,                                                     strict: false,                                                     from_attributes: false,                                                     loc_by_alias: true,                                                 },                                             ),                                             class: Py(                                                 0x0000555556df5690,                                             ),                                             post_init: None,                                             frozen: false,                                             custom_init: false,                                             root_model: false,                                             name: "IceServer",                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "IceServerInfoData",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x00005555572ffce0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         name: "IceServerInfoData",     }, ), definitions=[])[source]
__repr__()[source]

Return repr(self).

Return type:

str

__repr_args__()[source]
__repr_name__()[source]

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

Return type:

str

__repr_str__(join_str)[source]
Return type:

str

__rich_repr__()[source]

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

__setattr__(name, value)[source]

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)[source]
Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, ice_servers: List[kittycad.models.ice_server.IceServer]) -> None>[source]
__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')[source]
__str__()[source]

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>[source]
_calculate_keys(*args, **kwargs)[source]
Return type:

Any

_check_frozen(name, value)[source]
Return type:

None

_copy_and_set_values(*args, **kwargs)[source]
Return type:

Any

classmethod _get_value(cls, *args, **kwargs)[source]
Return type:

Any

_iter(*args, **kwargs)[source]
Return type:

Any

classmethod construct(cls, _fields_set=None, **values)[source]
Return type:

Model

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

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:
  • include (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to include in the copied model.

  • exclude (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to exclude in the copied model.

  • update (Dict[str, Any] | None) – Optional dictionary of field-value pairs to override field values in the copied model.

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

Return type:

Model

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)[source]
Return type:

Dict[str, Any]

classmethod from_orm(cls, obj)[source]
Return type:

Model

ice_servers: List[IceServer][source]
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)[source]
Return type:

str

property model_computed_fields: dict[str, ComputedFieldInfo][source]

Get the computed fields of this model instance.

Returns:

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}[source]

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

classmethod model_construct(_fields_set=None, **values)[source]

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. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Parameters:
  • _fields_set (set[str] | None) – The set of field names accepted for the Model instance.

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

Return type:

Model

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:
  • update (dict[str, Any] | None) – 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:

Model

Returns:

New model instance.

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

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump

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

Parameters:
  • mode – The mode in which to_python should run. If mode is ‘json’, the dictionary will only contain JSON serializable types. If mode is ‘python’, the dictionary may contain any Python objects.

  • include – A list of fields to include in the output.

  • exclude – A list of fields to exclude from the output.

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

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

  • exclude_defaults – Whether to exclude fields that are set to their default value from the output.

  • exclude_none – Whether to exclude fields that have a value of None from the output.

  • round_trip – Whether to enable serialization and deserialization round-trip support.

  • warnings – Whether to log warnings when invalid fields are encountered.

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump_json

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

Parameters:
  • indent – Indentation to use in the JSON output. If None is passed, the output will be compact.

  • include – Field(s) to include in the JSON output. Can take either a string or set of strings.

  • exclude – Field(s) to exclude from the JSON output. Can take either a string or set of strings.

  • by_alias – Whether to serialize using field aliases.

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

  • exclude_defaults – Whether to exclude fields that have the default value.

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

  • round_trip – Whether to use serialization/deserialization between JSON and class instance.

  • warnings – Whether to show any warnings that occurred during serialization.

Returns:

A JSON string representation of the model.

property model_extra[source]

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]] = {'ice_servers': FieldInfo(annotation=List[kittycad.models.ice_server.IceServer], required=True)}[source]

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str][source]

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')[source]

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)[source]

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)[source]

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)[source]

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 – Whether to force the rebuilding of the model schema, defaults to False.

  • raise_errors – Whether to raise errors, defaults to True.

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

  • _types_namespace – The types namespace, defaults to 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)[source]

Validate a pydantic model instance.

Parameters:
  • obj (Any) – The object to validate.

  • strict (bool | None) – Whether to raise an exception on invalid fields.

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

  • context (dict[str, Any] | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Model

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)[source]

Usage docs: https://docs.pydantic.dev/2.5/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 (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

Raises:

ValueError – If json_data is not a JSON string.

classmethod model_validate_strings(obj, *, strict=None, context=None)[source]

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

Parameters:
  • obj (Any) – The object contains string data to validate.

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

  • context (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

classmethod parse_file(cls, path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod parse_obj(cls, obj)[source]
Return type:

Model

classmethod parse_raw(cls, b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod schema(cls, by_alias=True, ref_template='#/$defs/{model}')[source]
Return type:

Dict[str, Any]

classmethod schema_json(cls, *, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)[source]
Return type:

str

classmethod update_forward_refs(cls, **localns)[source]
Return type:

None

classmethod validate(cls, value)[source]
Return type:

Model

class kittycad.models.ok_web_socket_response_data.MetricsRequestData(**data)[source][source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__abstractmethods__ = frozenset({})[source]
__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__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]', '__signature__': 'ClassVar[Signature]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]'}[source]
classmethod __class_getitem__(typevar_values)[source]
__class_vars__: ClassVar[set[str]] = {}[source]
__copy__()[source]

Returns a shallow copy of the model.

Return type:

Model

__deepcopy__(memo=None)[source]

Returns a deep copy of the model.

Return type:

Model

__delattr__(item)[source]

Implement delattr(self, name).

Return type:

Any

__dict__[source]
__eq__(other)[source]

Return self==value.

Return type:

bool

__fields__ = {}[source]
property __fields_set__: set[str][source]
classmethod __get_pydantic_core_schema__(_BaseModel__source, _BaseModel__handler)[source]

Hook into generating the model’s CoreSchema.

Parameters:
  • __source – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

  • __handler – Call into Pydantic’s internal JSON schema generation. A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TuplePositionalSchema, TupleVariableSchema, 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]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(_BaseModel__core_schema, _BaseModel__handler)[source]

Hook into generating the model’s JSON schema.

Parameters:
  • __core_schema – 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 – 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)[source]
Return type:

Any

__getstate__()[source]
Return type:

dict[Any, Any]

__hash__ = None[source]
__init__(**data)[source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__iter__()[source]

So dict(model) works.

Return type:

TupleGenerator

__module__ = 'kittycad.models.ok_web_socket_response_data'[source]
__pretty__(fmt, **kwargs)[source]

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

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[dict[str, ModelPrivateAttr]] = {}[source]
__pydantic_complete__: ClassVar[bool] = True[source]
__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.ok_web_socket_response_data.MetricsRequestData'>, 'config': {'title': 'MetricsRequestData'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_web_socket_response_data.MetricsRequestData'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_web_socket_response_data.MetricsRequestData'>>]}, 'ref': 'kittycad.models.ok_web_socket_response_data.MetricsRequestData:93825024129008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {}, 'model_name': 'MetricsRequestData', 'type': 'model-fields'}, 'type': 'model'}[source]
__pydantic_custom_init__: ClassVar[bool] = False[source]
__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})[source]
__pydantic_extra__: dict[str, Any] | None[source]
__pydantic_fields_set__: set[str][source]
__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}[source]
classmethod __pydantic_init_subclass__(**kwargs)[source]

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] = {'Annotated': <pydantic._internal._model_construction._PydanticWeakRef object>, 'BaseModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'ExportData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Field': <pydantic._internal._model_construction._PydanticWeakRef object>, 'IceServer': <pydantic._internal._model_construction._PydanticWeakRef object>, 'IceServerInfoData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'List': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Literal': <pydantic._internal._model_construction._PydanticWeakRef object>, 'ModelingData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'OkModelingCmdResponse': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RawFile': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RootModel': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcIceCandidateInit': <pydantic._internal._model_construction._PydanticWeakRef object>, 'RtcSessionDescription': <pydantic._internal._model_construction._PydanticWeakRef object>, 'SdpAnswerData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'TrickleIceData': <pydantic._internal._model_construction._PydanticWeakRef object>, 'Union': <pydantic._internal._model_construction._PydanticWeakRef object>, '__builtins__': {'ArithmeticError': <class 'ArithmeticError'>, 'AssertionError': <class 'AssertionError'>, 'AttributeError': <class 'AttributeError'>, 'BaseException': <class 'BaseException'>, 'BlockingIOError': <class 'BlockingIOError'>, 'BrokenPipeError': <class 'BrokenPipeError'>, 'BufferError': <class 'BufferError'>, 'BytesWarning': <class 'BytesWarning'>, 'ChildProcessError': <class 'ChildProcessError'>, 'ConnectionAbortedError': <class 'ConnectionAbortedError'>, 'ConnectionError': <class 'ConnectionError'>, 'ConnectionRefusedError': <class 'ConnectionRefusedError'>, 'ConnectionResetError': <class 'ConnectionResetError'>, 'DeprecationWarning': <class 'DeprecationWarning'>, 'EOFError': <class 'EOFError'>, 'Ellipsis': Ellipsis, 'EnvironmentError': <class 'OSError'>, 'Exception': <class 'Exception'>, 'False': False, 'FileExistsError': <class 'FileExistsError'>, 'FileNotFoundError': <class 'FileNotFoundError'>, 'FloatingPointError': <class 'FloatingPointError'>, 'FutureWarning': <class 'FutureWarning'>, 'GeneratorExit': <class 'GeneratorExit'>, 'IOError': <class 'OSError'>, 'ImportError': <class 'ImportError'>, 'ImportWarning': <class 'ImportWarning'>, 'IndentationError': <class 'IndentationError'>, 'IndexError': <class 'IndexError'>, 'InterruptedError': <class 'InterruptedError'>, 'IsADirectoryError': <class 'IsADirectoryError'>, 'KeyError': <class 'KeyError'>, 'KeyboardInterrupt': <class 'KeyboardInterrupt'>, 'LookupError': <class 'LookupError'>, 'MemoryError': <class 'MemoryError'>, 'ModuleNotFoundError': <class 'ModuleNotFoundError'>, 'NameError': <class 'NameError'>, 'None': None, 'NotADirectoryError': <class 'NotADirectoryError'>, 'NotImplemented': NotImplemented, 'NotImplementedError': <class 'NotImplementedError'>, 'OSError': <class 'OSError'>, 'OverflowError': <class 'OverflowError'>, 'PendingDeprecationWarning': <class 'PendingDeprecationWarning'>, 'PermissionError': <class 'PermissionError'>, 'ProcessLookupError': <class 'ProcessLookupError'>, 'RecursionError': <class 'RecursionError'>, 'ReferenceError': <class 'ReferenceError'>, 'ResourceWarning': <class 'ResourceWarning'>, 'RuntimeError': <class 'RuntimeError'>, 'RuntimeWarning': <class 'RuntimeWarning'>, 'StopAsyncIteration': <class 'StopAsyncIteration'>, 'StopIteration': <class 'StopIteration'>, 'SyntaxError': <class 'SyntaxError'>, 'SyntaxWarning': <class 'SyntaxWarning'>, 'SystemError': <class 'SystemError'>, 'SystemExit': <class 'SystemExit'>, 'TabError': <class 'TabError'>, 'TimeoutError': <class 'TimeoutError'>, 'True': True, 'TypeError': <class 'TypeError'>, 'UnboundLocalError': <class 'UnboundLocalError'>, 'UnicodeDecodeError': <class 'UnicodeDecodeError'>, 'UnicodeEncodeError': <class 'UnicodeEncodeError'>, 'UnicodeError': <class 'UnicodeError'>, 'UnicodeTranslateError': <class 'UnicodeTranslateError'>, 'UnicodeWarning': <class 'UnicodeWarning'>, 'UserWarning': <class 'UserWarning'>, 'ValueError': <class 'ValueError'>, 'Warning': <class 'Warning'>, 'ZeroDivisionError': <class 'ZeroDivisionError'>, '__build_class__': <built-in function __build_class__>, '__debug__': True, '__doc__': "Built-in functions, exceptions, and other objects.\n\nNoteworthy: None is the `nil' object; Ellipsis represents `...' in slices.", '__import__': <built-in function __import__>, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__name__': 'builtins', '__package__': '', '__spec__': ModuleSpec(name='builtins', loader=<class '_frozen_importlib.BuiltinImporter'>, origin='built-in'), 'abs': <built-in function abs>, 'all': <built-in function all>, 'any': <built-in function any>, 'ascii': <built-in function ascii>, 'bin': <built-in function bin>, 'bool': <class 'bool'>, 'breakpoint': <built-in function breakpoint>, 'bytearray': <class 'bytearray'>, 'bytes': <class 'bytes'>, 'callable': <built-in function callable>, 'chr': <built-in function chr>, 'classmethod': <class 'classmethod'>, 'compile': <built-in function compile>, 'complex': <class 'complex'>, 'copyright': Copyright (c) 2001-2023 Python Software Foundation. All Rights Reserved.  Copyright (c) 2000 BeOpen.com. All Rights Reserved.  Copyright (c) 1995-2001 Corporation for National Research Initiatives. All Rights Reserved.  Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam. All Rights Reserved., 'credits':     Thanks to CWI, CNRI, BeOpen.com, Zope Corporation and a cast of thousands     for supporting Python development.  See www.python.org for more information., 'delattr': <built-in function delattr>, 'dict': <class 'dict'>, 'dir': <built-in function dir>, 'divmod': <built-in function divmod>, 'enumerate': <class 'enumerate'>, 'eval': <built-in function eval>, 'exec': <built-in function exec>, 'exit': Use exit() or Ctrl-D (i.e. EOF) to exit, 'filter': <class 'filter'>, 'float': <class 'float'>, 'format': <built-in function format>, 'frozenset': <class 'frozenset'>, 'getattr': <built-in function getattr>, 'globals': <built-in function globals>, 'hasattr': <built-in function hasattr>, 'hash': <built-in function hash>, 'help': Type help() for interactive help, or help(object) for help about object., 'hex': <built-in function hex>, 'id': <built-in function id>, 'input': <built-in function input>, 'int': <class 'int'>, 'isinstance': <built-in function isinstance>, 'issubclass': <built-in function issubclass>, 'iter': <built-in function iter>, 'len': <built-in function len>, 'license': Type license() to see the full license text, 'list': <class 'list'>, 'locals': <built-in function locals>, 'map': <class 'map'>, 'max': <built-in function max>, 'memoryview': <class 'memoryview'>, 'min': <built-in function min>, 'next': <built-in function next>, 'object': <class 'object'>, 'oct': <built-in function oct>, 'open': <built-in function open>, 'ord': <built-in function ord>, 'pow': <built-in function pow>, 'print': <built-in function print>, 'property': <class 'property'>, 'quit': Use quit() or Ctrl-D (i.e. EOF) to exit, 'range': <class 'range'>, 'repr': <built-in function repr>, 'reversed': <class 'reversed'>, 'round': <built-in function round>, 'set': <class 'set'>, 'setattr': <built-in function setattr>, 'slice': <class 'slice'>, 'sorted': <built-in function sorted>, 'staticmethod': <class 'staticmethod'>, 'str': <class 'str'>, 'sum': <built-in function sum>, 'super': <class 'super'>, 'tuple': <class 'tuple'>, 'type': <class 'type'>, 'vars': <built-in function vars>, 'zip': <class 'zip'>}, '__cached__': '/home/user/src/kittycad/models/__pycache__/ok_web_socket_response_data.cpython-39.pyc', '__doc__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__file__': '/home/user/src/kittycad/models/ok_web_socket_response_data.py', '__loader__': <pydantic._internal._model_construction._PydanticWeakRef object>, '__name__': 'kittycad.models.ok_web_socket_response_data', '__package__': 'kittycad.models', '__spec__': <pydantic._internal._model_construction._PydanticWeakRef object>, 'export': <pydantic._internal._model_construction._PydanticWeakRef object>, 'ice_server_info': <pydantic._internal._model_construction._PydanticWeakRef object>, 'modeling': <pydantic._internal._model_construction._PydanticWeakRef object>, 'sdp_answer': <pydantic._internal._model_construction._PydanticWeakRef object>, 'trickle_ice': <pydantic._internal._model_construction._PydanticWeakRef object>}[source]
__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None[source]
__pydantic_private__: dict[str, Any] | None[source]
__pydantic_root_model__: ClassVar[bool] = False[source]
__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x00005555573bf7f0,         ),         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: "MetricsRequestData",     }, ), definitions=[])[source]
__pydantic_validator__: ClassVar[SchemaValidator] = SchemaValidator(title="MetricsRequestData", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [],                 model_name: "MetricsRequestData",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x00005555573bf7f0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         name: "MetricsRequestData",     }, ), definitions=[])[source]
__repr__()[source]

Return repr(self).

Return type:

str

__repr_args__()[source]
__repr_name__()[source]

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

Return type:

str

__repr_str__(join_str)[source]
Return type:

str

__rich_repr__()[source]

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

__setattr__(name, value)[source]

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)[source]
Return type:

None

__signature__: ClassVar[Signature] = <Signature () -> None>[source]
__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')[source]
__str__()[source]

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>[source]
_calculate_keys(*args, **kwargs)[source]
Return type:

Any

_check_frozen(name, value)[source]
Return type:

None

_copy_and_set_values(*args, **kwargs)[source]
Return type:

Any

classmethod _get_value(cls, *args, **kwargs)[source]
Return type:

Any

_iter(*args, **kwargs)[source]
Return type:

Any

classmethod construct(cls, _fields_set=None, **values)[source]
Return type:

Model

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

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:
  • include (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to include in the copied model.

  • exclude (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to exclude in the copied model.

  • update (Dict[str, Any] | None) – Optional dictionary of field-value pairs to override field values in the copied model.

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

Return type:

Model

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)[source]
Return type:

Dict[str, Any]

classmethod from_orm(cls, obj)[source]
Return type:

Model

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)[source]
Return type:

str

property model_computed_fields: dict[str, ComputedFieldInfo][source]

Get the computed fields of this model instance.

Returns:

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}[source]

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

classmethod model_construct(_fields_set=None, **values)[source]

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. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Parameters:
  • _fields_set (set[str] | None) – The set of field names accepted for the Model instance.

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

Return type:

Model

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:
  • update (dict[str, Any] | None) – 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:

Model

Returns:

New model instance.

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

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump

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

Parameters:
  • mode – The mode in which to_python should run. If mode is ‘json’, the dictionary will only contain JSON serializable types. If mode is ‘python’, the dictionary may contain any Python objects.

  • include – A list of fields to include in the output.

  • exclude – A list of fields to exclude from the output.

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

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

  • exclude_defaults – Whether to exclude fields that are set to their default value from the output.

  • exclude_none – Whether to exclude fields that have a value of None from the output.

  • round_trip – Whether to enable serialization and deserialization round-trip support.

  • warnings – Whether to log warnings when invalid fields are encountered.

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True)[source]

Usage docs: https://docs.pydantic.dev/2.5/concepts/serialization/#modelmodel_dump_json

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

Parameters:
  • indent – Indentation to use in the JSON output. If None is passed, the output will be compact.

  • include – Field(s) to include in the JSON output. Can take either a string or set of strings.

  • exclude – Field(s) to exclude from the JSON output. Can take either a string or set of strings.

  • by_alias – Whether to serialize using field aliases.

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

  • exclude_defaults – Whether to exclude fields that have the default value.

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

  • round_trip – Whether to use serialization/deserialization between JSON and class instance.

  • warnings – Whether to show any warnings that occurred during serialization.

Returns:

A JSON string representation of the model.

property model_extra[source]

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]] = {}[source]

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str][source]

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')[source]

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)[source]

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)[source]

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)[source]

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 – Whether to force the rebuilding of the model schema, defaults to False.

  • raise_errors – Whether to raise errors, defaults to True.

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

  • _types_namespace – The types namespace, defaults to 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)[source]

Validate a pydantic model instance.

Parameters:
  • obj (Any) – The object to validate.

  • strict (bool | None) – Whether to raise an exception on invalid fields.

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

  • context (dict[str, Any] | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Model

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)[source]

Usage docs: https://docs.pydantic.dev/2.5/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 (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

Raises:

ValueError – If json_data is not a JSON string.

classmethod model_validate_strings(obj, *, strict=None, context=None)[source]

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

Parameters:
  • obj (Any) – The object contains string data to validate.

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

  • context (dict[str, Any] | None) – Extra variables to pass to the validator.

Return type:

Model

Returns:

The validated Pydantic model.

classmethod parse_file(cls, path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod parse_obj(cls, obj)[source]
Return type:

Model

classmethod parse_raw(cls, b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)[source]
Return type:

Model

classmethod schema(cls, by_alias=True, ref_template='#/$defs/{model}')[source]
Return type:

Dict[str, Any]

classmethod schema_json(cls, *, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)[source]
Return type:

str

classmethod update_forward_refs(cls, **localns)[source]
Return type:

None

classmethod validate(cls, value)[source]
Return type:

Model

class kittycad.models.ok_web_socket_response_data.ModelingData(**data)[source][source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__abstractmethods__ = frozenset({})[source]
__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__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]', '__signature__': 'ClassVar[Signature]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'modeling_response': <class 'pydantic.root_model.RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>}[source]
classmethod __class_getitem__(typevar_values)[source]
__class_vars__: ClassVar[set[str]] = {}[source]
__copy__()[source]

Returns a shallow copy of the model.

Return type:

Model

__deepcopy__(memo=None)[source]

Returns a deep copy of the model.

Return type:

Model

__delattr__(item)[source]

Implement delattr(self, name).

Return type:

Any

__dict__[source]
__eq__(other)[source]

Return self==value.

Return type:

bool

__fields__ = {'modeling_response': FieldInfo(annotation=RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True)}[source]
property __fields_set__: set[str][source]
classmethod __get_pydantic_core_schema__(_BaseModel__source, _BaseModel__handler)[source]

Hook into generating the model’s CoreSchema.

Parameters:
  • __source – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

  • __handler – Call into Pydantic’s internal JSON schema generation. A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TuplePositionalSchema, TupleVariableSchema, 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]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(_BaseModel__core_schema, _BaseModel__handler)[source]

Hook into generating the model’s JSON schema.

Parameters:
  • __core_schema – 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 – 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)[source]
Return type:

Any

__getstate__()[source]
Return type:

dict[Any, Any]

__hash__ = None[source]
__init__(**data)[source]

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

__iter__()[source]

So dict(model) works.

Return type:

TupleGenerator

__module__ = 'kittycad.models.ok_web_socket_response_data'[source]
__pretty__(fmt, **kwargs)[source]

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

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[dict[str, ModelPrivateAttr]] = {}[source]
__pydantic_complete__: ClassVar[bool] = True[source]
__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'type': 'model', 'cls': <class 'kittycad.models.point3d.Point3d'>, 'schema': {'type': 'model-fields', 'fields': {'x': {'type': 'model-field', 'schema': {'type': 'float', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'y': {'type': 'model-field', 'schema': {'type': 'float', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'z': {'type': 'model-field', 'schema': {'type': 'float', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'Point3d', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'Point3d'}, 'ref': 'kittycad.models.point3d.Point3d:93825014233264', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}], 'schema': {'cls': <class 'kittycad.models.ok_web_socket_response_data.ModelingData'>, 'config': {'title': 'ModelingData'}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_web_socket_response_data.ModelingData'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_web_socket_response_data.ModelingData'>>]}, 'ref': 'kittycad.models.ok_web_socket_response_data.ModelingData:93825023436352', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'modeling_response': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'pydantic.root_model.RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'config': {'title': "RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, 'custom_init': False, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False, 'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'pydantic.root_model.RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:93825014829600[Annotated[Union[kittycad.models.ok_modeling_cmd_response.empty, kittycad.models.ok_modeling_cmd_response.export, kittycad.models.ok_modeling_cmd_response.select_with_point, kittycad.models.ok_modeling_cmd_response.highlight_set_entity, kittycad.models.ok_modeling_cmd_response.entity_get_child_uuid, kittycad.models.ok_modeling_cmd_response.entity_get_num_children, kittycad.models.ok_modeling_cmd_response.entity_get_parent_id, kittycad.models.ok_modeling_cmd_response.entity_get_all_child_uuids, kittycad.models.ok_modeling_cmd_response.select_get, kittycad.models.ok_modeling_cmd_response.get_entity_type, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_edge_faces, kittycad.models.ok_modeling_cmd_response.solid3d_get_all_opposite_edges, kittycad.models.ok_modeling_cmd_response.solid3d_get_opposite_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_prev_adjacent_edge, kittycad.models.ok_modeling_cmd_response.solid3d_get_next_adjacent_edge, kittycad.models.ok_modeling_cmd_response.mouse_click, kittycad.models.ok_modeling_cmd_response.curve_get_type, kittycad.models.ok_modeling_cmd_response.curve_get_control_points, kittycad.models.ok_modeling_cmd_response.take_snapshot, kittycad.models.ok_modeling_cmd_response.path_get_info, kittycad.models.ok_modeling_cmd_response.path_get_curve_uuids_for_vertices, kittycad.models.ok_modeling_cmd_response.path_get_vertex_uuids, kittycad.models.ok_modeling_cmd_response.plane_intersect_and_project, kittycad.models.ok_modeling_cmd_response.curve_get_end_points, kittycad.models.ok_modeling_cmd_response.import_files, kittycad.models.ok_modeling_cmd_response.mass, kittycad.models.ok_modeling_cmd_response.volume, kittycad.models.ok_modeling_cmd_response.density, kittycad.models.ok_modeling_cmd_response.surface_area, kittycad.models.ok_modeling_cmd_response.center_of_mass, kittycad.models.ok_modeling_cmd_response.get_sketch_mode_plane], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140736964689632]", 'root_model': True, 'schema': {'choices': [{'type': 'model', 'cls': <class 'kittycad.models.ok_modeling_cmd_response.empty'>, 'schema': {'type': 'model-fields', 'fields': {'type': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'literal', 'expected': ['empty'], 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': 'empty'}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'empty', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'empty'}, 'ref': 'kittycad.models.ok_modeling_cmd_response.empty:93825022365552', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_modeling_cmd_response.empty'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.empty'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, {'type': 'model', 'cls': <class 'kittycad.models.ok_modeling_cmd_response.export'>, 'schema': {'type': 'model-fields', 'fields': {'data': {'type': 'model-field', 'schema': {'type': 'model', 'cls': <class 'kittycad.models.export.Export'>, 'schema': {'type': 'model-fields', 'fields': {'files': {'type': 'model-field', 'schema': {'type': 'list', 'items_schema': {'type': 'model', 'cls': <class 'kittycad.models.export_file.ExportFile'>, 'schema': {'type': 'model-fields', 'fields': {'contents': {'type': 'model-field', 'schema': {'function': {'type': 'no-info', 'function': <class 'kittycad.models.base64data.Base64Data'>}, 'schema': {'type': 'bytes', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}, 'type': 'function-after'}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'name': {'type': 'model-field', 'schema': {'type': 'str', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'ExportFile', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'ExportFile'}, 'ref': 'kittycad.models.export_file.ExportFile:93825017379136', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.export_file.ExportFile'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export_file.ExportFile'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, 'strict': False}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'Export', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'Export'}, 'ref': 'kittycad.models.export.Export:93825017383472', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.export.Export'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.export.Export'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'type': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'literal', 'expected': ['export'], 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': 'export'}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'export', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'export'}, 'ref': 'kittycad.models.ok_modeling_cmd_response.export:93825022369840', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_modeling_cmd_response.export'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.export'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, {'type': 'model', 'cls': <class 'kittycad.models.ok_modeling_cmd_response.select_with_point'>, 'schema': {'type': 'model-fields', 'fields': {'data': {'type': 'model-field', 'schema': {'type': 'model', 'cls': <class 'kittycad.models.select_with_point.SelectWithPoint'>, 'schema': {'type': 'model-fields', 'fields': {'entity_id': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'nullable', 'schema': {'type': 'str', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': None}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'SelectWithPoint', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'SelectWithPoint'}, 'ref': 'kittycad.models.select_with_point.SelectWithPoint:93825022294256', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.select_with_point.SelectWithPoint'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.select_with_point.SelectWithPoint'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'type': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'literal', 'expected': ['select_with_point'], 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': 'select_with_point'}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'select_with_point', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'select_with_point'}, 'ref': 'kittycad.models.ok_modeling_cmd_response.select_with_point:93825022377952', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.ok_modeling_cmd_response.select_with_point'>), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.ok_modeling_cmd_response.select_with_point'>>], 'pydantic_js_annotation_functions': [], 'pydantic.internal.needs_apply_discriminated_union': False}}, {'type': 'model', 'cls': <class 'kittycad.models.ok_modeling_cmd_response.highlight_set_entity'>, 'schema': {'type': 'model-fields', 'fields': {'data': {'type': 'model-field', 'schema': {'type': 'model', 'cls': <class 'kittycad.models.highlight_set_entity.HighlightSetEntity'>, 'schema': {'type': 'model-fields', 'fields': {'entity_id': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'nullable', 'schema': {'type': 'str', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': None}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}, 'sequence': {'type': 'model-field', 'schema': {'type': 'default', 'schema': {'type': 'nullable', 'schema': {'type': 'int', 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'metadata': {'pydantic.internal.needs_apply_discriminated_union': False}}, 'default': None}, 'metadata': {'pydantic_js_functions': [], 'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>]}}}, 'model_name': 'HighlightSetEntity', 'computed_fields': []}, 'custom_init': False, 'root_model': False, 'config': {'title': 'HighlightSetEntity'}, 'ref': 'kittycad.models.highlight_set_entity.HighlightSetEntity:93825018048688', 'metadata': {'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class