Method __new__

pydantic/_internal/_model_construction.py:84–280

Metaclass for creating Pydantic models. Args: cls_name: The name of the class to be created. bases: The base classes of the class to be created. namespace: The attribute dictionary of the class to be created. __pydantic_generic_metadata__: Met

(
        mcs,
        cls_name: str,
        bases: tuple[type[Any], ...],
        namespace: dict[str, Any],
        __pydantic_generic_metadata__: PydanticGenericMetadata | None = None,
        __pydantic_reset_parent_namespace__: bool = True,
        _create_model_module: str | None = None,
        **kwargs: Any,
    )

@dataclass_transform(kw_only_default=True, field_specifiers=(PydanticModelField, PydanticModelPrivateAttr, NoInitField))
class ModelMetaclass(ABCMeta):
    def __new__(
        mcs,
        cls_name: str,
        bases: tuple[type[Any], ...],
        namespace: dict[str, Any],
        __pydantic_generic_metadata__: PydanticGenericMetadata | None = None,
        __pydantic_reset_parent_namespace__: bool = True,
        _create_model_module: str | None = None,
        **kwargs: Any,
    ) -> type:
        """Metaclass for creating Pydantic models.

        Args:
            cls_name: The name of the class to be created.
            bases: The base classes of the class to be created.
            namespace: The attribute dictionary of the class to be created.
            __pydantic_generic_metadata__: Metadata for generic models.
            __pydantic_reset_parent_namespace__: Reset parent namespace.
            _create_model_module: The module of the class to be created, if created by `create_model`.
            **kwargs: Catch-all for any other keyword arguments.

        Returns:
            The new class created by the metaclass.
        """
        # Note `ModelMetaclass` refers to `BaseModel`, but is also used to *create* `BaseModel`, so we rely on the fact
        # that `BaseModel` itself won't have any bases, but any subclass of it will, to determine whether the `__new__`
        # call we're in the middle of is for the `BaseModel` class.
        if bases:
            raw_annotations: dict[str, Any]
            if sys.version_info >= (3, 14):
                if (
                    '__annotations__' in namespace
                ):  # `from __future__ import annotations` was used in the model's module
                    raw_annotations = namespace['__annotations__']
                else:
                    # See https://docs.python.org/3.14/library/annotationlib.html#using-annotations-in-a-metaclass:
                    from annotationlib import Format, call_annotate_function, get_annotate_from_class_namespace

                    if annotate := get_annotate_from_class_namespace(namespace):
                        raw_annotations = call_annotate_function(annotate, format=Format.FORWARDREF)
                    else:
                        raw_annotations = {}
            else:
                raw_annotations = namespace.get('__annotations__', {})

            base_field_names, class_vars, base_private_attributes = mcs._collect_bases_data(bases)

            config_wrapper = ConfigWrapper.for_model(bases, namespace, raw_annotations, kwargs)
            namespace['model_config'] = config_wrapper.config_dict
            private_attributes = inspect_namespace(
                namespace, raw_annotations, config_wrapper.ignored_types, class_vars, base_field_names
            )
            if private_attributes or base_private_attributes:
                original_model_post_init = get_model_post_init(namespace, bases)
                if original_model_post_init is not None:
                    # if there are private attributes and a model_post_init function, we handle both

                    @wraps(original_model_post_init)