bpo-37049: PEP 589: Add TypedDict to typing module (GH-13573)
The implementation is straightforward and essentially is just copied from `typing_extensions`.
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@ -878,6 +878,39 @@ The module defines the following classes, functions and decorators:
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The ``_field_types`` and ``__annotations__`` attributes are
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The ``_field_types`` and ``__annotations__`` attributes are
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now regular dictionaries instead of instances of ``OrderedDict``.
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now regular dictionaries instead of instances of ``OrderedDict``.
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.. class:: TypedDict(dict)
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A simple typed namespace. At runtime it is equivalent to
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a plain :class:`dict`.
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``TypedDict`` creates a dictionary type that expects all of its
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instances to have a certain set of keys, where each key is
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associated with a value of a consistent type. This expectation
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is not checked at runtime but is only enforced by type checkers.
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Usage::
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class Point2D(TypedDict):
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x: int
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y: int
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label: str
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a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK
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b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check
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assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
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The type info for introspection can be accessed via ``Point2D.__annotations__``
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and ``Point2D.__total__``. To allow using this feature with older versions
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of Python that do not support :pep:`526`, ``TypedDict`` supports two additional
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equivalent syntactic forms::
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Point2D = TypedDict('Point2D', x=int, y=int, label=str)
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Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
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See :pep:`589` for more examples and detailed rules of using ``TypedDict``
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with type checkers.
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.. versionadded:: 3.8
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.. function:: NewType(typ)
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.. function:: NewType(typ)
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@ -18,7 +18,7 @@ from typing import get_type_hints
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from typing import no_type_check, no_type_check_decorator
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from typing import no_type_check, no_type_check_decorator
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from typing import Type
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from typing import Type
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from typing import NewType
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from typing import NewType
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from typing import NamedTuple
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from typing import NamedTuple, TypedDict
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from typing import IO, TextIO, BinaryIO
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from typing import IO, TextIO, BinaryIO
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from typing import Pattern, Match
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from typing import Pattern, Match
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import abc
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import abc
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@ -1883,6 +1883,18 @@ class XRepr(NamedTuple):
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def __add__(self, other):
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def __add__(self, other):
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return 0
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return 0
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Label = TypedDict('Label', [('label', str)])
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class Point2D(TypedDict):
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x: int
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y: int
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class LabelPoint2D(Point2D, Label): ...
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class Options(TypedDict, total=False):
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log_level: int
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log_path: str
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class HasForeignBaseClass(mod_generics_cache.A):
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class HasForeignBaseClass(mod_generics_cache.A):
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some_xrepr: 'XRepr'
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some_xrepr: 'XRepr'
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other_a: 'mod_generics_cache.A'
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other_a: 'mod_generics_cache.A'
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@ -2658,6 +2670,97 @@ class XMethBad2(NamedTuple):
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self.assertEqual(jane2, jane)
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self.assertEqual(jane2, jane)
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class TypedDictTests(BaseTestCase):
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def test_basics_functional_syntax(self):
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Emp = TypedDict('Emp', {'name': str, 'id': int})
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self.assertIsSubclass(Emp, dict)
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self.assertIsSubclass(Emp, typing.MutableMapping)
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self.assertNotIsSubclass(Emp, collections.abc.Sequence)
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jim = Emp(name='Jim', id=1)
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self.assertIs(type(jim), dict)
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self.assertEqual(jim['name'], 'Jim')
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self.assertEqual(jim['id'], 1)
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self.assertEqual(Emp.__name__, 'Emp')
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self.assertEqual(Emp.__module__, __name__)
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self.assertEqual(Emp.__bases__, (dict,))
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self.assertEqual(Emp.__annotations__, {'name': str, 'id': int})
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self.assertEqual(Emp.__total__, True)
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def test_basics_keywords_syntax(self):
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Emp = TypedDict('Emp', name=str, id=int)
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self.assertIsSubclass(Emp, dict)
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self.assertIsSubclass(Emp, typing.MutableMapping)
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self.assertNotIsSubclass(Emp, collections.abc.Sequence)
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jim = Emp(name='Jim', id=1)
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self.assertIs(type(jim), dict)
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self.assertEqual(jim['name'], 'Jim')
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self.assertEqual(jim['id'], 1)
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self.assertEqual(Emp.__name__, 'Emp')
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self.assertEqual(Emp.__module__, __name__)
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self.assertEqual(Emp.__bases__, (dict,))
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self.assertEqual(Emp.__annotations__, {'name': str, 'id': int})
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self.assertEqual(Emp.__total__, True)
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def test_typeddict_errors(self):
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Emp = TypedDict('Emp', {'name': str, 'id': int})
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self.assertEqual(TypedDict.__module__, 'typing')
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jim = Emp(name='Jim', id=1)
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with self.assertRaises(TypeError):
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isinstance({}, Emp)
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with self.assertRaises(TypeError):
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isinstance(jim, Emp)
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with self.assertRaises(TypeError):
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issubclass(dict, Emp)
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with self.assertRaises(TypeError):
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TypedDict('Hi', x=1)
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with self.assertRaises(TypeError):
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TypedDict('Hi', [('x', int), ('y', 1)])
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with self.assertRaises(TypeError):
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TypedDict('Hi', [('x', int)], y=int)
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def test_py36_class_syntax_usage(self):
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self.assertEqual(LabelPoint2D.__name__, 'LabelPoint2D')
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self.assertEqual(LabelPoint2D.__module__, __name__)
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self.assertEqual(LabelPoint2D.__annotations__, {'x': int, 'y': int, 'label': str})
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self.assertEqual(LabelPoint2D.__bases__, (dict,))
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self.assertEqual(LabelPoint2D.__total__, True)
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self.assertNotIsSubclass(LabelPoint2D, typing.Sequence)
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not_origin = Point2D(x=0, y=1)
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self.assertEqual(not_origin['x'], 0)
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self.assertEqual(not_origin['y'], 1)
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other = LabelPoint2D(x=0, y=1, label='hi')
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self.assertEqual(other['label'], 'hi')
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def test_pickle(self):
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global EmpD # pickle wants to reference the class by name
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EmpD = TypedDict('EmpD', name=str, id=int)
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jane = EmpD({'name': 'jane', 'id': 37})
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for proto in range(pickle.HIGHEST_PROTOCOL + 1):
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z = pickle.dumps(jane, proto)
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jane2 = pickle.loads(z)
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self.assertEqual(jane2, jane)
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self.assertEqual(jane2, {'name': 'jane', 'id': 37})
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ZZ = pickle.dumps(EmpD, proto)
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EmpDnew = pickle.loads(ZZ)
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self.assertEqual(EmpDnew({'name': 'jane', 'id': 37}), jane)
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def test_optional(self):
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EmpD = TypedDict('EmpD', name=str, id=int)
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self.assertEqual(typing.Optional[EmpD], typing.Union[None, EmpD])
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self.assertNotEqual(typing.List[EmpD], typing.Tuple[EmpD])
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def test_total(self):
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D = TypedDict('D', {'x': int}, total=False)
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self.assertEqual(D(), {})
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self.assertEqual(D(x=1), {'x': 1})
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self.assertEqual(D.__total__, False)
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self.assertEqual(Options(), {})
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self.assertEqual(Options(log_level=2), {'log_level': 2})
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self.assertEqual(Options.__total__, False)
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class IOTests(BaseTestCase):
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class IOTests(BaseTestCase):
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def test_io(self):
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def test_io(self):
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@ -89,6 +89,7 @@ __all__ = [
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'Set',
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'Set',
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'FrozenSet',
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'FrozenSet',
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'NamedTuple', # Not really a type.
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'NamedTuple', # Not really a type.
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'TypedDict', # Not really a type.
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'Generator',
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'Generator',
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# One-off things.
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# One-off things.
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@ -1490,6 +1491,89 @@ class NamedTuple(metaclass=NamedTupleMeta):
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return _make_nmtuple(typename, fields)
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return _make_nmtuple(typename, fields)
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def _dict_new(cls, *args, **kwargs):
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return dict(*args, **kwargs)
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def _typeddict_new(cls, _typename, _fields=None, **kwargs):
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total = kwargs.pop('total', True)
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if _fields is None:
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_fields = kwargs
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elif kwargs:
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raise TypeError("TypedDict takes either a dict or keyword arguments,"
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" but not both")
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ns = {'__annotations__': dict(_fields), '__total__': total}
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try:
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# Setting correct module is necessary to make typed dict classes pickleable.
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ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
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except (AttributeError, ValueError):
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pass
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return _TypedDictMeta(_typename, (), ns)
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def _check_fails(cls, other):
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# Typed dicts are only for static structural subtyping.
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raise TypeError('TypedDict does not support instance and class checks')
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class _TypedDictMeta(type):
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def __new__(cls, name, bases, ns, total=True):
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"""Create new typed dict class object.
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This method is called directly when TypedDict is subclassed,
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or via _typeddict_new when TypedDict is instantiated. This way
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TypedDict supports all three syntax forms described in its docstring.
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Subclasses and instances of TypedDict return actual dictionaries
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via _dict_new.
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"""
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ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new
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tp_dict = super(_TypedDictMeta, cls).__new__(cls, name, (dict,), ns)
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anns = ns.get('__annotations__', {})
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msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
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anns = {n: _type_check(tp, msg) for n, tp in anns.items()}
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for base in bases:
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anns.update(base.__dict__.get('__annotations__', {}))
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tp_dict.__annotations__ = anns
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if not hasattr(tp_dict, '__total__'):
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tp_dict.__total__ = total
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return tp_dict
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__instancecheck__ = __subclasscheck__ = _check_fails
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class TypedDict(dict, metaclass=_TypedDictMeta):
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"""A simple typed namespace. At runtime it is equivalent to a plain dict.
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TypedDict creates a dictionary type that expects all of its
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instances to have a certain set of keys, where each key is
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associated with a value of a consistent type. This expectation
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is not checked at runtime but is only enforced by type checkers.
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Usage::
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class Point2D(TypedDict):
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x: int
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y: int
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label: str
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a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK
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b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check
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assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
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The type info can be accessed via Point2D.__annotations__. TypedDict
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supports two additional equivalent forms::
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Point2D = TypedDict('Point2D', x=int, y=int, label=str)
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Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
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The class syntax is only supported in Python 3.6+, while two other
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syntax forms work for Python 2.7 and 3.2+
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"""
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def NewType(name, tp):
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def NewType(name, tp):
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"""NewType creates simple unique types with almost zero
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"""NewType creates simple unique types with almost zero
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runtime overhead. NewType(name, tp) is considered a subtype of tp
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runtime overhead. NewType(name, tp) is considered a subtype of tp
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@ -0,0 +1 @@
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PEP 589: Add ``TypedDict`` to the ``typing`` module.
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