from typing import TYPE_CHECKING, Any, Dict, FrozenSet, NamedTuple, Type from .fields import Required from .main import BaseModel, create_model if TYPE_CHECKING: class TypedDict(Dict[str, Any]): __annotations__: Dict[str, Type[Any]] __total__: bool __required_keys__: FrozenSet[str] __optional_keys__: FrozenSet[str] def create_model_from_typeddict(typeddict_cls: Type['TypedDict'], **kwargs: Any) -> Type['BaseModel']: """ Create a `BaseModel` based on the fields of a `TypedDict`. Since `typing.TypedDict` in Python 3.8 does not store runtime information about optional keys, we raise an error if this happens (see https://bugs.python.org/issue38834). """ field_definitions: Dict[str, Any] # Best case scenario: with python 3.9+ or when `TypedDict` is imported from `typing_extensions` if not hasattr(typeddict_cls, '__required_keys__'): raise TypeError( 'You should use `typing_extensions.TypedDict` instead of `typing.TypedDict`. ' 'Without it, there is no way to differentiate required and optional fields when subclassed.' ) field_definitions = { field_name: (field_type, Required if field_name in typeddict_cls.__required_keys__ else None) for field_name, field_type in typeddict_cls.__annotations__.items() } return create_model(typeddict_cls.__name__, **kwargs, **field_definitions) def create_model_from_namedtuple(namedtuple_cls: Type['NamedTuple'], **kwargs: Any) -> Type['BaseModel']: """ Create a `BaseModel` based on the fields of a named tuple. A named tuple can be created with `typing.NamedTuple` and declared annotations but also with `collections.namedtuple`, in this case we consider all fields to have type `Any`. """ namedtuple_annotations: Dict[str, Type[Any]] = getattr( namedtuple_cls, '__annotations__', {k: Any for k in namedtuple_cls._fields} ) field_definitions: Dict[str, Any] = { field_name: (field_type, Required) for field_name, field_type in namedtuple_annotations.items() } return create_model(namedtuple_cls.__name__, **kwargs, **field_definitions)