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JelleZijlstradebonte
JelleZijlstra
and
debonte
authored
add dataclass_transform (#1054)
Co-authored-by: Erik De Bonte <[email protected]>
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‎typing_extensions/CHANGELOG‎

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# Release 4.x.x
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- Runtime support for PEP 681 and `typing_extensions.dataclass_transform`.
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- `Annotated` can now wrap `ClassVar` and `Final`. Backport from
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bpo-46491. Patch by Gregory Beauregard (@GBeauregard).
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- Add missed `Required` and `NotRequired` to `__all__`. Patch by

‎typing_extensions/README.rst‎

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- Experimental features
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- ``@dataclass_transform()`` (see PEP 681)
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- ``NotRequired`` (see PEP 655)
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- ``Required`` (see PEP 655)
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- ``Self`` (see PEP 673)

‎typing_extensions/src/test_typing_extensions.py‎

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from typing_extensions import TypeAlias, ParamSpec, Concatenate, ParamSpecArgs, ParamSpecKwargs, TypeGuard
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from typing_extensions import Awaitable, AsyncIterator, AsyncContextManager, Required, NotRequired
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from typing_extensions import Protocol, runtime, runtime_checkable, Annotated, overload, final, is_typeddict
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from typing_extensions import dataclass_transform
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try:
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from typing_extensions import get_type_hints
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except ImportError:
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self.assertIs(True, Methods.cached.__final__)
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class DataclassTransformTests(BaseTestCase):
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def test_decorator(self):
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def create_model(*, frozen: bool = False, kw_only: bool = True):
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return lambda cls: cls
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decorated = dataclass_transform(kw_only_default=True, order_default=False)(create_model)
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class CustomerModel:
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id: int
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self.assertIs(decorated, create_model)
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self.assertEqual(
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decorated.__dataclass_transform__,
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{
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"eq_default": True,
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"order_default": False,
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"kw_only_default": True,
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"field_descriptors": (),
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}
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)
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self.assertIs(
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decorated(frozen=True, kw_only=False)(CustomerModel),
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CustomerModel
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)
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def test_base_class(self):
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class ModelBase:
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def __init_subclass__(cls, *, frozen: bool = False): ...
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Decorated = dataclass_transform(eq_default=True, order_default=True)(ModelBase)
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class CustomerModel(Decorated, frozen=True):
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id: int
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self.assertIs(Decorated, ModelBase)
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self.assertEqual(
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Decorated.__dataclass_transform__,
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{
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"eq_default": True,
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"order_default": True,
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"kw_only_default": False,
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"field_descriptors": (),
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}
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)
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self.assertIsSubclass(CustomerModel, Decorated)
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def test_metaclass(self):
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class Field: ...
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class ModelMeta(type):
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def __new__(
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cls, name, bases, namespace, *, init: bool = True,
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):
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return super().__new__(cls, name, bases, namespace)
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Decorated = dataclass_transform(
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order_default=True, field_descriptors=(Field,)
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)(ModelMeta)
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class ModelBase(metaclass=Decorated): ...
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class CustomerModel(ModelBase, init=False):
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id: int
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self.assertIs(Decorated, ModelMeta)
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self.assertEqual(
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Decorated.__dataclass_transform__,
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{
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"eq_default": True,
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"order_default": True,
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"kw_only_default": False,
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"field_descriptors": (Field,),
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}
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)
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self.assertIsInstance(CustomerModel, Decorated)
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class AllTests(BaseTestCase):
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def test_typing_extensions_includes_standard(self):

‎typing_extensions/src/typing_extensions.py‎

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# One-off things.
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'Annotated',
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'dataclass_transform',
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'final',
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'IntVar',
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'is_typeddict',
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Required = _Required(_root=True)
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NotRequired = _NotRequired(_root=True)
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if hasattr(typing, 'dataclass_transform'):
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dataclass_transform = typing.dataclass_transform
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else:
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def dataclass_transform(
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*,
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eq_default: bool = True,
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order_default: bool = False,
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kw_only_default: bool = False,
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field_descriptors: typing.Tuple[
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typing.Union[typing.Type[typing.Any], typing.Callable[..., typing.Any]],
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...
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] = (),
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) -> typing.Callable[[T], T]:
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"""Decorator that marks a function, class, or metaclass as providing
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dataclass-like behavior.
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Example:
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from typing_extensions import dataclass_transform
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_T = TypeVar("_T")
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# Used on a decorator function
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@dataclass_transform()
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def create_model(cls: type[_T]) -> type[_T]:
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...
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return cls
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@create_model
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class CustomerModel:
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id: int
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name: str
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# Used on a base class
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@dataclass_transform()
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class ModelBase: ...
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class CustomerModel(ModelBase):
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id: int
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name: str
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# Used on a metaclass
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@dataclass_transform()
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class ModelMeta(type): ...
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class ModelBase(metaclass=ModelMeta): ...
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class CustomerModel(ModelBase):
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id: int
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name: str
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Each of the ``CustomerModel`` classes defined in this example will now
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behave similarly to a dataclass created with the ``@dataclasses.dataclass``
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decorator. For example, the type checker will synthesize an ``__init__``
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method.
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The arguments to this decorator can be used to customize this behavior:
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- ``eq_default`` indicates whether the ``eq`` parameter is assumed to be
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True or False if it is omitted by the caller.
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- ``order_default`` indicates whether the ``order`` parameter is
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assumed to be True or False if it is omitted by the caller.
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- ``kw_only_default`` indicates whether the ``kw_only`` parameter is
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assumed to be True or False if it is omitted by the caller.
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- ``field_descriptors`` specifies a static list of supported classes
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or functions, that describe fields, similar to ``dataclasses.field()``.
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At runtime, this decorator records its arguments in the
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``__dataclass_transform__`` attribute on the decorated object.
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See PEP 681 for details.
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"""
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def decorator(cls_or_fn):
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cls_or_fn.__dataclass_transform__ = {
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"eq_default": eq_default,
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"order_default": order_default,
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"kw_only_default": kw_only_default,
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"field_descriptors": field_descriptors,
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}
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return cls_or_fn
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return decorator

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