mirror of
https://github.com/morpheus65535/bazarr
synced 2024-12-27 01:57:33 +00:00
2209 lines
78 KiB
Python
2209 lines
78 KiB
Python
import abc
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import collections
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import collections.abc
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import functools
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import operator
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import sys
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import types as _types
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import typing
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__all__ = [
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# Super-special typing primitives.
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'Any',
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'ClassVar',
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'Concatenate',
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'Final',
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'LiteralString',
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'ParamSpec',
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'ParamSpecArgs',
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'ParamSpecKwargs',
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'Self',
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'Type',
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'TypeVar',
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'TypeVarTuple',
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'Unpack',
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# ABCs (from collections.abc).
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'Awaitable',
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'AsyncIterator',
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'AsyncIterable',
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'Coroutine',
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'AsyncGenerator',
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'AsyncContextManager',
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'ChainMap',
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# Concrete collection types.
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'ContextManager',
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'Counter',
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'Deque',
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'DefaultDict',
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'NamedTuple',
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'OrderedDict',
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'TypedDict',
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# Structural checks, a.k.a. protocols.
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'SupportsIndex',
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# One-off things.
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'Annotated',
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'assert_never',
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'assert_type',
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'clear_overloads',
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'dataclass_transform',
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'get_overloads',
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'final',
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'get_args',
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'get_origin',
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'get_type_hints',
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'IntVar',
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'is_typeddict',
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'Literal',
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'NewType',
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'overload',
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'override',
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'Protocol',
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'reveal_type',
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'runtime',
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'runtime_checkable',
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'Text',
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'TypeAlias',
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'TypeGuard',
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'TYPE_CHECKING',
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'Never',
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'NoReturn',
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'Required',
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'NotRequired',
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]
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# for backward compatibility
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PEP_560 = True
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GenericMeta = type
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# The functions below are modified copies of typing internal helpers.
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# They are needed by _ProtocolMeta and they provide support for PEP 646.
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_marker = object()
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def _check_generic(cls, parameters, elen=_marker):
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"""Check correct count for parameters of a generic cls (internal helper).
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This gives a nice error message in case of count mismatch.
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"""
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if not elen:
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raise TypeError(f"{cls} is not a generic class")
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if elen is _marker:
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if not hasattr(cls, "__parameters__") or not cls.__parameters__:
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raise TypeError(f"{cls} is not a generic class")
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elen = len(cls.__parameters__)
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alen = len(parameters)
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if alen != elen:
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if hasattr(cls, "__parameters__"):
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parameters = [p for p in cls.__parameters__ if not _is_unpack(p)]
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num_tv_tuples = sum(isinstance(p, TypeVarTuple) for p in parameters)
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if (num_tv_tuples > 0) and (alen >= elen - num_tv_tuples):
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return
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raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};"
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f" actual {alen}, expected {elen}")
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if sys.version_info >= (3, 10):
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def _should_collect_from_parameters(t):
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return isinstance(
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t, (typing._GenericAlias, _types.GenericAlias, _types.UnionType)
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)
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elif sys.version_info >= (3, 9):
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def _should_collect_from_parameters(t):
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return isinstance(t, (typing._GenericAlias, _types.GenericAlias))
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else:
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def _should_collect_from_parameters(t):
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return isinstance(t, typing._GenericAlias) and not t._special
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def _collect_type_vars(types, typevar_types=None):
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"""Collect all type variable contained in types in order of
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first appearance (lexicographic order). For example::
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_collect_type_vars((T, List[S, T])) == (T, S)
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"""
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if typevar_types is None:
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typevar_types = typing.TypeVar
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tvars = []
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for t in types:
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if (
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isinstance(t, typevar_types) and
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t not in tvars and
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not _is_unpack(t)
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):
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tvars.append(t)
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if _should_collect_from_parameters(t):
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tvars.extend([t for t in t.__parameters__ if t not in tvars])
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return tuple(tvars)
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NoReturn = typing.NoReturn
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# Some unconstrained type variables. These are used by the container types.
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# (These are not for export.)
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T = typing.TypeVar('T') # Any type.
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KT = typing.TypeVar('KT') # Key type.
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VT = typing.TypeVar('VT') # Value type.
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T_co = typing.TypeVar('T_co', covariant=True) # Any type covariant containers.
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T_contra = typing.TypeVar('T_contra', contravariant=True) # Ditto contravariant.
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if sys.version_info >= (3, 11):
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from typing import Any
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else:
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class _AnyMeta(type):
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def __instancecheck__(self, obj):
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if self is Any:
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raise TypeError("typing_extensions.Any cannot be used with isinstance()")
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return super().__instancecheck__(obj)
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def __repr__(self):
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if self is Any:
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return "typing_extensions.Any"
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return super().__repr__()
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class Any(metaclass=_AnyMeta):
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"""Special type indicating an unconstrained type.
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- Any is compatible with every type.
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- Any assumed to have all methods.
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- All values assumed to be instances of Any.
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Note that all the above statements are true from the point of view of
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static type checkers. At runtime, Any should not be used with instance
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checks.
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"""
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def __new__(cls, *args, **kwargs):
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if cls is Any:
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raise TypeError("Any cannot be instantiated")
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return super().__new__(cls, *args, **kwargs)
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ClassVar = typing.ClassVar
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# On older versions of typing there is an internal class named "Final".
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# 3.8+
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if hasattr(typing, 'Final') and sys.version_info[:2] >= (3, 7):
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Final = typing.Final
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# 3.7
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else:
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class _FinalForm(typing._SpecialForm, _root=True):
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def __repr__(self):
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return 'typing_extensions.' + self._name
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def __getitem__(self, parameters):
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item = typing._type_check(parameters,
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f'{self._name} accepts only a single type.')
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return typing._GenericAlias(self, (item,))
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Final = _FinalForm('Final',
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doc="""A special typing construct to indicate that a name
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cannot be re-assigned or overridden in a subclass.
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For example:
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MAX_SIZE: Final = 9000
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MAX_SIZE += 1 # Error reported by type checker
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class Connection:
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TIMEOUT: Final[int] = 10
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class FastConnector(Connection):
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TIMEOUT = 1 # Error reported by type checker
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There is no runtime checking of these properties.""")
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if sys.version_info >= (3, 11):
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final = typing.final
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else:
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# @final exists in 3.8+, but we backport it for all versions
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# before 3.11 to keep support for the __final__ attribute.
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# See https://bugs.python.org/issue46342
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def final(f):
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"""This decorator can be used to indicate to type checkers that
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the decorated method cannot be overridden, and decorated class
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cannot be subclassed. For example:
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class Base:
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@final
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def done(self) -> None:
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...
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class Sub(Base):
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def done(self) -> None: # Error reported by type checker
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...
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@final
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class Leaf:
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...
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class Other(Leaf): # Error reported by type checker
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...
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There is no runtime checking of these properties. The decorator
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sets the ``__final__`` attribute to ``True`` on the decorated object
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to allow runtime introspection.
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"""
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try:
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f.__final__ = True
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except (AttributeError, TypeError):
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# Skip the attribute silently if it is not writable.
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# AttributeError happens if the object has __slots__ or a
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# read-only property, TypeError if it's a builtin class.
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pass
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return f
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def IntVar(name):
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return typing.TypeVar(name)
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# 3.8+:
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if hasattr(typing, 'Literal'):
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Literal = typing.Literal
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# 3.7:
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else:
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class _LiteralForm(typing._SpecialForm, _root=True):
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def __repr__(self):
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return 'typing_extensions.' + self._name
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def __getitem__(self, parameters):
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return typing._GenericAlias(self, parameters)
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Literal = _LiteralForm('Literal',
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doc="""A type that can be used to indicate to type checkers
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that the corresponding value has a value literally equivalent
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to the provided parameter. For example:
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var: Literal[4] = 4
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The type checker understands that 'var' is literally equal to
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the value 4 and no other value.
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Literal[...] cannot be subclassed. There is no runtime
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checking verifying that the parameter is actually a value
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instead of a type.""")
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_overload_dummy = typing._overload_dummy # noqa
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if hasattr(typing, "get_overloads"): # 3.11+
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overload = typing.overload
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get_overloads = typing.get_overloads
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clear_overloads = typing.clear_overloads
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else:
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# {module: {qualname: {firstlineno: func}}}
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_overload_registry = collections.defaultdict(
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functools.partial(collections.defaultdict, dict)
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)
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def overload(func):
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"""Decorator for overloaded functions/methods.
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In a stub file, place two or more stub definitions for the same
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function in a row, each decorated with @overload. For example:
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@overload
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def utf8(value: None) -> None: ...
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@overload
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def utf8(value: bytes) -> bytes: ...
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@overload
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def utf8(value: str) -> bytes: ...
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In a non-stub file (i.e. a regular .py file), do the same but
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follow it with an implementation. The implementation should *not*
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be decorated with @overload. For example:
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@overload
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def utf8(value: None) -> None: ...
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@overload
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def utf8(value: bytes) -> bytes: ...
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@overload
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def utf8(value: str) -> bytes: ...
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def utf8(value):
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# implementation goes here
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The overloads for a function can be retrieved at runtime using the
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get_overloads() function.
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"""
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# classmethod and staticmethod
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f = getattr(func, "__func__", func)
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try:
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_overload_registry[f.__module__][f.__qualname__][
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f.__code__.co_firstlineno
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] = func
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except AttributeError:
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# Not a normal function; ignore.
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pass
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return _overload_dummy
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def get_overloads(func):
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"""Return all defined overloads for *func* as a sequence."""
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# classmethod and staticmethod
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f = getattr(func, "__func__", func)
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if f.__module__ not in _overload_registry:
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return []
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mod_dict = _overload_registry[f.__module__]
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if f.__qualname__ not in mod_dict:
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return []
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return list(mod_dict[f.__qualname__].values())
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def clear_overloads():
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"""Clear all overloads in the registry."""
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_overload_registry.clear()
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# This is not a real generic class. Don't use outside annotations.
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Type = typing.Type
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# Various ABCs mimicking those in collections.abc.
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# A few are simply re-exported for completeness.
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Awaitable = typing.Awaitable
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Coroutine = typing.Coroutine
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AsyncIterable = typing.AsyncIterable
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AsyncIterator = typing.AsyncIterator
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Deque = typing.Deque
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ContextManager = typing.ContextManager
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AsyncContextManager = typing.AsyncContextManager
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DefaultDict = typing.DefaultDict
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# 3.7.2+
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if hasattr(typing, 'OrderedDict'):
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OrderedDict = typing.OrderedDict
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# 3.7.0-3.7.2
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else:
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OrderedDict = typing._alias(collections.OrderedDict, (KT, VT))
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Counter = typing.Counter
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ChainMap = typing.ChainMap
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AsyncGenerator = typing.AsyncGenerator
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NewType = typing.NewType
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Text = typing.Text
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TYPE_CHECKING = typing.TYPE_CHECKING
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_PROTO_WHITELIST = ['Callable', 'Awaitable',
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'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator',
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'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',
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'ContextManager', 'AsyncContextManager']
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def _get_protocol_attrs(cls):
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attrs = set()
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for base in cls.__mro__[:-1]: # without object
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if base.__name__ in ('Protocol', 'Generic'):
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continue
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annotations = getattr(base, '__annotations__', {})
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for attr in list(base.__dict__.keys()) + list(annotations.keys()):
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if (not attr.startswith('_abc_') and attr not in (
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'__abstractmethods__', '__annotations__', '__weakref__',
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'_is_protocol', '_is_runtime_protocol', '__dict__',
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'__args__', '__slots__',
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'__next_in_mro__', '__parameters__', '__origin__',
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'__orig_bases__', '__extra__', '__tree_hash__',
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'__doc__', '__subclasshook__', '__init__', '__new__',
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'__module__', '_MutableMapping__marker', '_gorg')):
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attrs.add(attr)
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return attrs
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def _is_callable_members_only(cls):
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return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls))
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def _maybe_adjust_parameters(cls):
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"""Helper function used in Protocol.__init_subclass__ and _TypedDictMeta.__new__.
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The contents of this function are very similar
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to logic found in typing.Generic.__init_subclass__
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on the CPython main branch.
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"""
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tvars = []
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if '__orig_bases__' in cls.__dict__:
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tvars = typing._collect_type_vars(cls.__orig_bases__)
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# Look for Generic[T1, ..., Tn] or Protocol[T1, ..., Tn].
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# If found, tvars must be a subset of it.
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# If not found, tvars is it.
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# Also check for and reject plain Generic,
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# and reject multiple Generic[...] and/or Protocol[...].
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gvars = None
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for base in cls.__orig_bases__:
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if (isinstance(base, typing._GenericAlias) and
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base.__origin__ in (typing.Generic, Protocol)):
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# for error messages
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the_base = base.__origin__.__name__
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if gvars is not None:
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raise TypeError(
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"Cannot inherit from Generic[...]"
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" and/or Protocol[...] multiple types.")
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gvars = base.__parameters__
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if gvars is None:
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gvars = tvars
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else:
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tvarset = set(tvars)
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gvarset = set(gvars)
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if not tvarset <= gvarset:
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s_vars = ', '.join(str(t) for t in tvars if t not in gvarset)
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s_args = ', '.join(str(g) for g in gvars)
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raise TypeError(f"Some type variables ({s_vars}) are"
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f" not listed in {the_base}[{s_args}]")
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tvars = gvars
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cls.__parameters__ = tuple(tvars)
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|
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# 3.8+
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if hasattr(typing, 'Protocol'):
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Protocol = typing.Protocol
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# 3.7
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else:
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def _no_init(self, *args, **kwargs):
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if type(self)._is_protocol:
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raise TypeError('Protocols cannot be instantiated')
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|
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class _ProtocolMeta(abc.ABCMeta): # noqa: B024
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# This metaclass is a bit unfortunate and exists only because of the lack
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# of __instancehook__.
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def __instancecheck__(cls, instance):
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# We need this method for situations where attributes are
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# assigned in __init__.
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if ((not getattr(cls, '_is_protocol', False) or
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_is_callable_members_only(cls)) and
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issubclass(instance.__class__, cls)):
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return True
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if cls._is_protocol:
|
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if all(hasattr(instance, attr) and
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(not callable(getattr(cls, attr, None)) or
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getattr(instance, attr) is not None)
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for attr in _get_protocol_attrs(cls)):
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return True
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return super().__instancecheck__(instance)
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|
|
class Protocol(metaclass=_ProtocolMeta):
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# There is quite a lot of overlapping code with typing.Generic.
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|
# Unfortunately it is hard to avoid this while these live in two different
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# modules. The duplicated code will be removed when Protocol is moved to typing.
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"""Base class for protocol classes. Protocol classes are defined as::
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class Proto(Protocol):
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def meth(self) -> int:
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...
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|
Such classes are primarily used with static type checkers that recognize
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|
structural subtyping (static duck-typing), for example::
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|
|
class C:
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|
def meth(self) -> int:
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return 0
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|
|
def func(x: Proto) -> int:
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return x.meth()
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|
|
func(C()) # Passes static type check
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|
|
See PEP 544 for details. Protocol classes decorated with
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|
@typing_extensions.runtime act as simple-minded runtime protocol that checks
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|
only the presence of given attributes, ignoring their type signatures.
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|
|
Protocol classes can be generic, they are defined as::
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|
|
class GenProto(Protocol[T]):
|
|
def meth(self) -> T:
|
|
...
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|
"""
|
|
__slots__ = ()
|
|
_is_protocol = True
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|
|
def __new__(cls, *args, **kwds):
|
|
if cls is Protocol:
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|
raise TypeError("Type Protocol cannot be instantiated; "
|
|
"it can only be used as a base class")
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return super().__new__(cls)
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|
|
@typing._tp_cache
|
|
def __class_getitem__(cls, params):
|
|
if not isinstance(params, tuple):
|
|
params = (params,)
|
|
if not params and cls is not typing.Tuple:
|
|
raise TypeError(
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f"Parameter list to {cls.__qualname__}[...] cannot be empty")
|
|
msg = "Parameters to generic types must be types."
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|
params = tuple(typing._type_check(p, msg) for p in params) # noqa
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|
if cls is Protocol:
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|
# Generic can only be subscripted with unique type variables.
|
|
if not all(isinstance(p, typing.TypeVar) for p in params):
|
|
i = 0
|
|
while isinstance(params[i], typing.TypeVar):
|
|
i += 1
|
|
raise TypeError(
|
|
"Parameters to Protocol[...] must all be type variables."
|
|
f" Parameter {i + 1} is {params[i]}")
|
|
if len(set(params)) != len(params):
|
|
raise TypeError(
|
|
"Parameters to Protocol[...] must all be unique")
|
|
else:
|
|
# Subscripting a regular Generic subclass.
|
|
_check_generic(cls, params, len(cls.__parameters__))
|
|
return typing._GenericAlias(cls, params)
|
|
|
|
def __init_subclass__(cls, *args, **kwargs):
|
|
if '__orig_bases__' in cls.__dict__:
|
|
error = typing.Generic in cls.__orig_bases__
|
|
else:
|
|
error = typing.Generic in cls.__bases__
|
|
if error:
|
|
raise TypeError("Cannot inherit from plain Generic")
|
|
_maybe_adjust_parameters(cls)
|
|
|
|
# Determine if this is a protocol or a concrete subclass.
|
|
if not cls.__dict__.get('_is_protocol', None):
|
|
cls._is_protocol = any(b is Protocol for b in cls.__bases__)
|
|
|
|
# Set (or override) the protocol subclass hook.
|
|
def _proto_hook(other):
|
|
if not cls.__dict__.get('_is_protocol', None):
|
|
return NotImplemented
|
|
if not getattr(cls, '_is_runtime_protocol', False):
|
|
if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']:
|
|
return NotImplemented
|
|
raise TypeError("Instance and class checks can only be used with"
|
|
" @runtime protocols")
|
|
if not _is_callable_members_only(cls):
|
|
if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']:
|
|
return NotImplemented
|
|
raise TypeError("Protocols with non-method members"
|
|
" don't support issubclass()")
|
|
if not isinstance(other, type):
|
|
# Same error as for issubclass(1, int)
|
|
raise TypeError('issubclass() arg 1 must be a class')
|
|
for attr in _get_protocol_attrs(cls):
|
|
for base in other.__mro__:
|
|
if attr in base.__dict__:
|
|
if base.__dict__[attr] is None:
|
|
return NotImplemented
|
|
break
|
|
annotations = getattr(base, '__annotations__', {})
|
|
if (isinstance(annotations, typing.Mapping) and
|
|
attr in annotations and
|
|
isinstance(other, _ProtocolMeta) and
|
|
other._is_protocol):
|
|
break
|
|
else:
|
|
return NotImplemented
|
|
return True
|
|
if '__subclasshook__' not in cls.__dict__:
|
|
cls.__subclasshook__ = _proto_hook
|
|
|
|
# We have nothing more to do for non-protocols.
|
|
if not cls._is_protocol:
|
|
return
|
|
|
|
# Check consistency of bases.
|
|
for base in cls.__bases__:
|
|
if not (base in (object, typing.Generic) or
|
|
base.__module__ == 'collections.abc' and
|
|
base.__name__ in _PROTO_WHITELIST or
|
|
isinstance(base, _ProtocolMeta) and base._is_protocol):
|
|
raise TypeError('Protocols can only inherit from other'
|
|
f' protocols, got {repr(base)}')
|
|
cls.__init__ = _no_init
|
|
|
|
|
|
# 3.8+
|
|
if hasattr(typing, 'runtime_checkable'):
|
|
runtime_checkable = typing.runtime_checkable
|
|
# 3.7
|
|
else:
|
|
def runtime_checkable(cls):
|
|
"""Mark a protocol class as a runtime protocol, so that it
|
|
can be used with isinstance() and issubclass(). Raise TypeError
|
|
if applied to a non-protocol class.
|
|
|
|
This allows a simple-minded structural check very similar to the
|
|
one-offs in collections.abc such as Hashable.
|
|
"""
|
|
if not isinstance(cls, _ProtocolMeta) or not cls._is_protocol:
|
|
raise TypeError('@runtime_checkable can be only applied to protocol classes,'
|
|
f' got {cls!r}')
|
|
cls._is_runtime_protocol = True
|
|
return cls
|
|
|
|
|
|
# Exists for backwards compatibility.
|
|
runtime = runtime_checkable
|
|
|
|
|
|
# 3.8+
|
|
if hasattr(typing, 'SupportsIndex'):
|
|
SupportsIndex = typing.SupportsIndex
|
|
# 3.7
|
|
else:
|
|
@runtime_checkable
|
|
class SupportsIndex(Protocol):
|
|
__slots__ = ()
|
|
|
|
@abc.abstractmethod
|
|
def __index__(self) -> int:
|
|
pass
|
|
|
|
|
|
if hasattr(typing, "Required"):
|
|
# The standard library TypedDict in Python 3.8 does not store runtime information
|
|
# about which (if any) keys are optional. See https://bugs.python.org/issue38834
|
|
# The standard library TypedDict in Python 3.9.0/1 does not honour the "total"
|
|
# keyword with old-style TypedDict(). See https://bugs.python.org/issue42059
|
|
# The standard library TypedDict below Python 3.11 does not store runtime
|
|
# information about optional and required keys when using Required or NotRequired.
|
|
# Generic TypedDicts are also impossible using typing.TypedDict on Python <3.11.
|
|
TypedDict = typing.TypedDict
|
|
_TypedDictMeta = typing._TypedDictMeta
|
|
is_typeddict = typing.is_typeddict
|
|
else:
|
|
def _check_fails(cls, other):
|
|
try:
|
|
if sys._getframe(1).f_globals['__name__'] not in ['abc',
|
|
'functools',
|
|
'typing']:
|
|
# Typed dicts are only for static structural subtyping.
|
|
raise TypeError('TypedDict does not support instance and class checks')
|
|
except (AttributeError, ValueError):
|
|
pass
|
|
return False
|
|
|
|
def _dict_new(*args, **kwargs):
|
|
if not args:
|
|
raise TypeError('TypedDict.__new__(): not enough arguments')
|
|
_, args = args[0], args[1:] # allow the "cls" keyword be passed
|
|
return dict(*args, **kwargs)
|
|
|
|
_dict_new.__text_signature__ = '($cls, _typename, _fields=None, /, **kwargs)'
|
|
|
|
def _typeddict_new(*args, total=True, **kwargs):
|
|
if not args:
|
|
raise TypeError('TypedDict.__new__(): not enough arguments')
|
|
_, args = args[0], args[1:] # allow the "cls" keyword be passed
|
|
if args:
|
|
typename, args = args[0], args[1:] # allow the "_typename" keyword be passed
|
|
elif '_typename' in kwargs:
|
|
typename = kwargs.pop('_typename')
|
|
import warnings
|
|
warnings.warn("Passing '_typename' as keyword argument is deprecated",
|
|
DeprecationWarning, stacklevel=2)
|
|
else:
|
|
raise TypeError("TypedDict.__new__() missing 1 required positional "
|
|
"argument: '_typename'")
|
|
if args:
|
|
try:
|
|
fields, = args # allow the "_fields" keyword be passed
|
|
except ValueError:
|
|
raise TypeError('TypedDict.__new__() takes from 2 to 3 '
|
|
f'positional arguments but {len(args) + 2} '
|
|
'were given')
|
|
elif '_fields' in kwargs and len(kwargs) == 1:
|
|
fields = kwargs.pop('_fields')
|
|
import warnings
|
|
warnings.warn("Passing '_fields' as keyword argument is deprecated",
|
|
DeprecationWarning, stacklevel=2)
|
|
else:
|
|
fields = None
|
|
|
|
if fields is None:
|
|
fields = kwargs
|
|
elif kwargs:
|
|
raise TypeError("TypedDict takes either a dict or keyword arguments,"
|
|
" but not both")
|
|
|
|
ns = {'__annotations__': dict(fields)}
|
|
try:
|
|
# Setting correct module is necessary to make typed dict classes pickleable.
|
|
ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
pass
|
|
|
|
return _TypedDictMeta(typename, (), ns, total=total)
|
|
|
|
_typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,'
|
|
' /, *, total=True, **kwargs)')
|
|
|
|
class _TypedDictMeta(type):
|
|
def __init__(cls, name, bases, ns, total=True):
|
|
super().__init__(name, bases, ns)
|
|
|
|
def __new__(cls, name, bases, ns, total=True):
|
|
# Create new typed dict class object.
|
|
# This method is called directly when TypedDict is subclassed,
|
|
# or via _typeddict_new when TypedDict is instantiated. This way
|
|
# TypedDict supports all three syntaxes described in its docstring.
|
|
# Subclasses and instances of TypedDict return actual dictionaries
|
|
# via _dict_new.
|
|
ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new
|
|
# Don't insert typing.Generic into __bases__ here,
|
|
# or Generic.__init_subclass__ will raise TypeError
|
|
# in the super().__new__() call.
|
|
# Instead, monkey-patch __bases__ onto the class after it's been created.
|
|
tp_dict = super().__new__(cls, name, (dict,), ns)
|
|
|
|
if any(issubclass(base, typing.Generic) for base in bases):
|
|
tp_dict.__bases__ = (typing.Generic, dict)
|
|
_maybe_adjust_parameters(tp_dict)
|
|
|
|
annotations = {}
|
|
own_annotations = ns.get('__annotations__', {})
|
|
msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
|
|
own_annotations = {
|
|
n: typing._type_check(tp, msg) for n, tp in own_annotations.items()
|
|
}
|
|
required_keys = set()
|
|
optional_keys = set()
|
|
|
|
for base in bases:
|
|
annotations.update(base.__dict__.get('__annotations__', {}))
|
|
required_keys.update(base.__dict__.get('__required_keys__', ()))
|
|
optional_keys.update(base.__dict__.get('__optional_keys__', ()))
|
|
|
|
annotations.update(own_annotations)
|
|
for annotation_key, annotation_type in own_annotations.items():
|
|
annotation_origin = get_origin(annotation_type)
|
|
if annotation_origin is Annotated:
|
|
annotation_args = get_args(annotation_type)
|
|
if annotation_args:
|
|
annotation_type = annotation_args[0]
|
|
annotation_origin = get_origin(annotation_type)
|
|
|
|
if annotation_origin is Required:
|
|
required_keys.add(annotation_key)
|
|
elif annotation_origin is NotRequired:
|
|
optional_keys.add(annotation_key)
|
|
elif total:
|
|
required_keys.add(annotation_key)
|
|
else:
|
|
optional_keys.add(annotation_key)
|
|
|
|
tp_dict.__annotations__ = annotations
|
|
tp_dict.__required_keys__ = frozenset(required_keys)
|
|
tp_dict.__optional_keys__ = frozenset(optional_keys)
|
|
if not hasattr(tp_dict, '__total__'):
|
|
tp_dict.__total__ = total
|
|
return tp_dict
|
|
|
|
__instancecheck__ = __subclasscheck__ = _check_fails
|
|
|
|
TypedDict = _TypedDictMeta('TypedDict', (dict,), {})
|
|
TypedDict.__module__ = __name__
|
|
TypedDict.__doc__ = \
|
|
"""A simple typed name space. At runtime it is equivalent to a plain dict.
|
|
|
|
TypedDict creates a dictionary type that expects all of its
|
|
instances to have a certain set of keys, with each key
|
|
associated with a value of a consistent type. This expectation
|
|
is not checked at runtime but is only enforced by type checkers.
|
|
Usage::
|
|
|
|
class Point2D(TypedDict):
|
|
x: int
|
|
y: int
|
|
label: str
|
|
|
|
a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK
|
|
b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check
|
|
|
|
assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
|
|
|
|
The type info can be accessed via the Point2D.__annotations__ dict, and
|
|
the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets.
|
|
TypedDict supports two additional equivalent forms::
|
|
|
|
Point2D = TypedDict('Point2D', x=int, y=int, label=str)
|
|
Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
|
|
|
|
The class syntax is only supported in Python 3.6+, while two other
|
|
syntax forms work for Python 2.7 and 3.2+
|
|
"""
|
|
|
|
if hasattr(typing, "_TypedDictMeta"):
|
|
_TYPEDDICT_TYPES = (typing._TypedDictMeta, _TypedDictMeta)
|
|
else:
|
|
_TYPEDDICT_TYPES = (_TypedDictMeta,)
|
|
|
|
def is_typeddict(tp):
|
|
"""Check if an annotation is a TypedDict class
|
|
|
|
For example::
|
|
class Film(TypedDict):
|
|
title: str
|
|
year: int
|
|
|
|
is_typeddict(Film) # => True
|
|
is_typeddict(Union[list, str]) # => False
|
|
"""
|
|
return isinstance(tp, tuple(_TYPEDDICT_TYPES))
|
|
|
|
|
|
if hasattr(typing, "assert_type"):
|
|
assert_type = typing.assert_type
|
|
|
|
else:
|
|
def assert_type(__val, __typ):
|
|
"""Assert (to the type checker) that the value is of the given type.
|
|
|
|
When the type checker encounters a call to assert_type(), it
|
|
emits an error if the value is not of the specified type::
|
|
|
|
def greet(name: str) -> None:
|
|
assert_type(name, str) # ok
|
|
assert_type(name, int) # type checker error
|
|
|
|
At runtime this returns the first argument unchanged and otherwise
|
|
does nothing.
|
|
"""
|
|
return __val
|
|
|
|
|
|
if hasattr(typing, "Required"):
|
|
get_type_hints = typing.get_type_hints
|
|
else:
|
|
import functools
|
|
import types
|
|
|
|
# replaces _strip_annotations()
|
|
def _strip_extras(t):
|
|
"""Strips Annotated, Required and NotRequired from a given type."""
|
|
if isinstance(t, _AnnotatedAlias):
|
|
return _strip_extras(t.__origin__)
|
|
if hasattr(t, "__origin__") and t.__origin__ in (Required, NotRequired):
|
|
return _strip_extras(t.__args__[0])
|
|
if isinstance(t, typing._GenericAlias):
|
|
stripped_args = tuple(_strip_extras(a) for a in t.__args__)
|
|
if stripped_args == t.__args__:
|
|
return t
|
|
return t.copy_with(stripped_args)
|
|
if hasattr(types, "GenericAlias") and isinstance(t, types.GenericAlias):
|
|
stripped_args = tuple(_strip_extras(a) for a in t.__args__)
|
|
if stripped_args == t.__args__:
|
|
return t
|
|
return types.GenericAlias(t.__origin__, stripped_args)
|
|
if hasattr(types, "UnionType") and isinstance(t, types.UnionType):
|
|
stripped_args = tuple(_strip_extras(a) for a in t.__args__)
|
|
if stripped_args == t.__args__:
|
|
return t
|
|
return functools.reduce(operator.or_, stripped_args)
|
|
|
|
return t
|
|
|
|
def get_type_hints(obj, globalns=None, localns=None, include_extras=False):
|
|
"""Return type hints for an object.
|
|
|
|
This is often the same as obj.__annotations__, but it handles
|
|
forward references encoded as string literals, adds Optional[t] if a
|
|
default value equal to None is set and recursively replaces all
|
|
'Annotated[T, ...]', 'Required[T]' or 'NotRequired[T]' with 'T'
|
|
(unless 'include_extras=True').
|
|
|
|
The argument may be a module, class, method, or function. The annotations
|
|
are returned as a dictionary. For classes, annotations include also
|
|
inherited members.
|
|
|
|
TypeError is raised if the argument is not of a type that can contain
|
|
annotations, and an empty dictionary is returned if no annotations are
|
|
present.
|
|
|
|
BEWARE -- the behavior of globalns and localns is counterintuitive
|
|
(unless you are familiar with how eval() and exec() work). The
|
|
search order is locals first, then globals.
|
|
|
|
- If no dict arguments are passed, an attempt is made to use the
|
|
globals from obj (or the respective module's globals for classes),
|
|
and these are also used as the locals. If the object does not appear
|
|
to have globals, an empty dictionary is used.
|
|
|
|
- If one dict argument is passed, it is used for both globals and
|
|
locals.
|
|
|
|
- If two dict arguments are passed, they specify globals and
|
|
locals, respectively.
|
|
"""
|
|
if hasattr(typing, "Annotated"):
|
|
hint = typing.get_type_hints(
|
|
obj, globalns=globalns, localns=localns, include_extras=True
|
|
)
|
|
else:
|
|
hint = typing.get_type_hints(obj, globalns=globalns, localns=localns)
|
|
if include_extras:
|
|
return hint
|
|
return {k: _strip_extras(t) for k, t in hint.items()}
|
|
|
|
|
|
# Python 3.9+ has PEP 593 (Annotated)
|
|
if hasattr(typing, 'Annotated'):
|
|
Annotated = typing.Annotated
|
|
# Not exported and not a public API, but needed for get_origin() and get_args()
|
|
# to work.
|
|
_AnnotatedAlias = typing._AnnotatedAlias
|
|
# 3.7-3.8
|
|
else:
|
|
class _AnnotatedAlias(typing._GenericAlias, _root=True):
|
|
"""Runtime representation of an annotated type.
|
|
|
|
At its core 'Annotated[t, dec1, dec2, ...]' is an alias for the type 't'
|
|
with extra annotations. The alias behaves like a normal typing alias,
|
|
instantiating is the same as instantiating the underlying type, binding
|
|
it to types is also the same.
|
|
"""
|
|
def __init__(self, origin, metadata):
|
|
if isinstance(origin, _AnnotatedAlias):
|
|
metadata = origin.__metadata__ + metadata
|
|
origin = origin.__origin__
|
|
super().__init__(origin, origin)
|
|
self.__metadata__ = metadata
|
|
|
|
def copy_with(self, params):
|
|
assert len(params) == 1
|
|
new_type = params[0]
|
|
return _AnnotatedAlias(new_type, self.__metadata__)
|
|
|
|
def __repr__(self):
|
|
return (f"typing_extensions.Annotated[{typing._type_repr(self.__origin__)}, "
|
|
f"{', '.join(repr(a) for a in self.__metadata__)}]")
|
|
|
|
def __reduce__(self):
|
|
return operator.getitem, (
|
|
Annotated, (self.__origin__,) + self.__metadata__
|
|
)
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, _AnnotatedAlias):
|
|
return NotImplemented
|
|
if self.__origin__ != other.__origin__:
|
|
return False
|
|
return self.__metadata__ == other.__metadata__
|
|
|
|
def __hash__(self):
|
|
return hash((self.__origin__, self.__metadata__))
|
|
|
|
class Annotated:
|
|
"""Add context specific metadata to a type.
|
|
|
|
Example: Annotated[int, runtime_check.Unsigned] indicates to the
|
|
hypothetical runtime_check module that this type is an unsigned int.
|
|
Every other consumer of this type can ignore this metadata and treat
|
|
this type as int.
|
|
|
|
The first argument to Annotated must be a valid type (and will be in
|
|
the __origin__ field), the remaining arguments are kept as a tuple in
|
|
the __extra__ field.
|
|
|
|
Details:
|
|
|
|
- It's an error to call `Annotated` with less than two arguments.
|
|
- Nested Annotated are flattened::
|
|
|
|
Annotated[Annotated[T, Ann1, Ann2], Ann3] == Annotated[T, Ann1, Ann2, Ann3]
|
|
|
|
- Instantiating an annotated type is equivalent to instantiating the
|
|
underlying type::
|
|
|
|
Annotated[C, Ann1](5) == C(5)
|
|
|
|
- Annotated can be used as a generic type alias::
|
|
|
|
Optimized = Annotated[T, runtime.Optimize()]
|
|
Optimized[int] == Annotated[int, runtime.Optimize()]
|
|
|
|
OptimizedList = Annotated[List[T], runtime.Optimize()]
|
|
OptimizedList[int] == Annotated[List[int], runtime.Optimize()]
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
def __new__(cls, *args, **kwargs):
|
|
raise TypeError("Type Annotated cannot be instantiated.")
|
|
|
|
@typing._tp_cache
|
|
def __class_getitem__(cls, params):
|
|
if not isinstance(params, tuple) or len(params) < 2:
|
|
raise TypeError("Annotated[...] should be used "
|
|
"with at least two arguments (a type and an "
|
|
"annotation).")
|
|
allowed_special_forms = (ClassVar, Final)
|
|
if get_origin(params[0]) in allowed_special_forms:
|
|
origin = params[0]
|
|
else:
|
|
msg = "Annotated[t, ...]: t must be a type."
|
|
origin = typing._type_check(params[0], msg)
|
|
metadata = tuple(params[1:])
|
|
return _AnnotatedAlias(origin, metadata)
|
|
|
|
def __init_subclass__(cls, *args, **kwargs):
|
|
raise TypeError(
|
|
f"Cannot subclass {cls.__module__}.Annotated"
|
|
)
|
|
|
|
# Python 3.8 has get_origin() and get_args() but those implementations aren't
|
|
# Annotated-aware, so we can't use those. Python 3.9's versions don't support
|
|
# ParamSpecArgs and ParamSpecKwargs, so only Python 3.10's versions will do.
|
|
if sys.version_info[:2] >= (3, 10):
|
|
get_origin = typing.get_origin
|
|
get_args = typing.get_args
|
|
# 3.7-3.9
|
|
else:
|
|
try:
|
|
# 3.9+
|
|
from typing import _BaseGenericAlias
|
|
except ImportError:
|
|
_BaseGenericAlias = typing._GenericAlias
|
|
try:
|
|
# 3.9+
|
|
from typing import GenericAlias as _typing_GenericAlias
|
|
except ImportError:
|
|
_typing_GenericAlias = typing._GenericAlias
|
|
|
|
def get_origin(tp):
|
|
"""Get the unsubscripted version of a type.
|
|
|
|
This supports generic types, Callable, Tuple, Union, Literal, Final, ClassVar
|
|
and Annotated. Return None for unsupported types. Examples::
|
|
|
|
get_origin(Literal[42]) is Literal
|
|
get_origin(int) is None
|
|
get_origin(ClassVar[int]) is ClassVar
|
|
get_origin(Generic) is Generic
|
|
get_origin(Generic[T]) is Generic
|
|
get_origin(Union[T, int]) is Union
|
|
get_origin(List[Tuple[T, T]][int]) == list
|
|
get_origin(P.args) is P
|
|
"""
|
|
if isinstance(tp, _AnnotatedAlias):
|
|
return Annotated
|
|
if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias, _BaseGenericAlias,
|
|
ParamSpecArgs, ParamSpecKwargs)):
|
|
return tp.__origin__
|
|
if tp is typing.Generic:
|
|
return typing.Generic
|
|
return None
|
|
|
|
def get_args(tp):
|
|
"""Get type arguments with all substitutions performed.
|
|
|
|
For unions, basic simplifications used by Union constructor are performed.
|
|
Examples::
|
|
get_args(Dict[str, int]) == (str, int)
|
|
get_args(int) == ()
|
|
get_args(Union[int, Union[T, int], str][int]) == (int, str)
|
|
get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int])
|
|
get_args(Callable[[], T][int]) == ([], int)
|
|
"""
|
|
if isinstance(tp, _AnnotatedAlias):
|
|
return (tp.__origin__,) + tp.__metadata__
|
|
if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias)):
|
|
if getattr(tp, "_special", False):
|
|
return ()
|
|
res = tp.__args__
|
|
if get_origin(tp) is collections.abc.Callable and res[0] is not Ellipsis:
|
|
res = (list(res[:-1]), res[-1])
|
|
return res
|
|
return ()
|
|
|
|
|
|
# 3.10+
|
|
if hasattr(typing, 'TypeAlias'):
|
|
TypeAlias = typing.TypeAlias
|
|
# 3.9
|
|
elif sys.version_info[:2] >= (3, 9):
|
|
class _TypeAliasForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
@_TypeAliasForm
|
|
def TypeAlias(self, parameters):
|
|
"""Special marker indicating that an assignment should
|
|
be recognized as a proper type alias definition by type
|
|
checkers.
|
|
|
|
For example::
|
|
|
|
Predicate: TypeAlias = Callable[..., bool]
|
|
|
|
It's invalid when used anywhere except as in the example above.
|
|
"""
|
|
raise TypeError(f"{self} is not subscriptable")
|
|
# 3.7-3.8
|
|
else:
|
|
class _TypeAliasForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
TypeAlias = _TypeAliasForm('TypeAlias',
|
|
doc="""Special marker indicating that an assignment should
|
|
be recognized as a proper type alias definition by type
|
|
checkers.
|
|
|
|
For example::
|
|
|
|
Predicate: TypeAlias = Callable[..., bool]
|
|
|
|
It's invalid when used anywhere except as in the example
|
|
above.""")
|
|
|
|
|
|
class _DefaultMixin:
|
|
"""Mixin for TypeVarLike defaults."""
|
|
|
|
__slots__ = ()
|
|
|
|
def __init__(self, default):
|
|
if isinstance(default, (tuple, list)):
|
|
self.__default__ = tuple((typing._type_check(d, "Default must be a type")
|
|
for d in default))
|
|
elif default:
|
|
self.__default__ = typing._type_check(default, "Default must be a type")
|
|
else:
|
|
self.__default__ = None
|
|
|
|
|
|
# Add default and infer_variance parameters from PEP 696 and 695
|
|
class TypeVar(typing.TypeVar, _DefaultMixin, _root=True):
|
|
"""Type variable."""
|
|
|
|
__module__ = 'typing'
|
|
|
|
def __init__(self, name, *constraints, bound=None,
|
|
covariant=False, contravariant=False,
|
|
default=None, infer_variance=False):
|
|
super().__init__(name, *constraints, bound=bound, covariant=covariant,
|
|
contravariant=contravariant)
|
|
_DefaultMixin.__init__(self, default)
|
|
self.__infer_variance__ = infer_variance
|
|
|
|
# for pickling:
|
|
try:
|
|
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
def_mod = None
|
|
if def_mod != 'typing_extensions':
|
|
self.__module__ = def_mod
|
|
|
|
|
|
# Python 3.10+ has PEP 612
|
|
if hasattr(typing, 'ParamSpecArgs'):
|
|
ParamSpecArgs = typing.ParamSpecArgs
|
|
ParamSpecKwargs = typing.ParamSpecKwargs
|
|
# 3.7-3.9
|
|
else:
|
|
class _Immutable:
|
|
"""Mixin to indicate that object should not be copied."""
|
|
__slots__ = ()
|
|
|
|
def __copy__(self):
|
|
return self
|
|
|
|
def __deepcopy__(self, memo):
|
|
return self
|
|
|
|
class ParamSpecArgs(_Immutable):
|
|
"""The args for a ParamSpec object.
|
|
|
|
Given a ParamSpec object P, P.args is an instance of ParamSpecArgs.
|
|
|
|
ParamSpecArgs objects have a reference back to their ParamSpec:
|
|
|
|
P.args.__origin__ is P
|
|
|
|
This type is meant for runtime introspection and has no special meaning to
|
|
static type checkers.
|
|
"""
|
|
def __init__(self, origin):
|
|
self.__origin__ = origin
|
|
|
|
def __repr__(self):
|
|
return f"{self.__origin__.__name__}.args"
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, ParamSpecArgs):
|
|
return NotImplemented
|
|
return self.__origin__ == other.__origin__
|
|
|
|
class ParamSpecKwargs(_Immutable):
|
|
"""The kwargs for a ParamSpec object.
|
|
|
|
Given a ParamSpec object P, P.kwargs is an instance of ParamSpecKwargs.
|
|
|
|
ParamSpecKwargs objects have a reference back to their ParamSpec:
|
|
|
|
P.kwargs.__origin__ is P
|
|
|
|
This type is meant for runtime introspection and has no special meaning to
|
|
static type checkers.
|
|
"""
|
|
def __init__(self, origin):
|
|
self.__origin__ = origin
|
|
|
|
def __repr__(self):
|
|
return f"{self.__origin__.__name__}.kwargs"
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, ParamSpecKwargs):
|
|
return NotImplemented
|
|
return self.__origin__ == other.__origin__
|
|
|
|
# 3.10+
|
|
if hasattr(typing, 'ParamSpec'):
|
|
|
|
# Add default Parameter - PEP 696
|
|
class ParamSpec(typing.ParamSpec, _DefaultMixin, _root=True):
|
|
"""Parameter specification variable."""
|
|
|
|
__module__ = 'typing'
|
|
|
|
def __init__(self, name, *, bound=None, covariant=False, contravariant=False,
|
|
default=None):
|
|
super().__init__(name, bound=bound, covariant=covariant,
|
|
contravariant=contravariant)
|
|
_DefaultMixin.__init__(self, default)
|
|
|
|
# for pickling:
|
|
try:
|
|
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
def_mod = None
|
|
if def_mod != 'typing_extensions':
|
|
self.__module__ = def_mod
|
|
|
|
# 3.7-3.9
|
|
else:
|
|
|
|
# Inherits from list as a workaround for Callable checks in Python < 3.9.2.
|
|
class ParamSpec(list, _DefaultMixin):
|
|
"""Parameter specification variable.
|
|
|
|
Usage::
|
|
|
|
P = ParamSpec('P')
|
|
|
|
Parameter specification variables exist primarily for the benefit of static
|
|
type checkers. They are used to forward the parameter types of one
|
|
callable to another callable, a pattern commonly found in higher order
|
|
functions and decorators. They are only valid when used in ``Concatenate``,
|
|
or s the first argument to ``Callable``. In Python 3.10 and higher,
|
|
they are also supported in user-defined Generics at runtime.
|
|
See class Generic for more information on generic types. An
|
|
example for annotating a decorator::
|
|
|
|
T = TypeVar('T')
|
|
P = ParamSpec('P')
|
|
|
|
def add_logging(f: Callable[P, T]) -> Callable[P, T]:
|
|
'''A type-safe decorator to add logging to a function.'''
|
|
def inner(*args: P.args, **kwargs: P.kwargs) -> T:
|
|
logging.info(f'{f.__name__} was called')
|
|
return f(*args, **kwargs)
|
|
return inner
|
|
|
|
@add_logging
|
|
def add_two(x: float, y: float) -> float:
|
|
'''Add two numbers together.'''
|
|
return x + y
|
|
|
|
Parameter specification variables defined with covariant=True or
|
|
contravariant=True can be used to declare covariant or contravariant
|
|
generic types. These keyword arguments are valid, but their actual semantics
|
|
are yet to be decided. See PEP 612 for details.
|
|
|
|
Parameter specification variables can be introspected. e.g.:
|
|
|
|
P.__name__ == 'T'
|
|
P.__bound__ == None
|
|
P.__covariant__ == False
|
|
P.__contravariant__ == False
|
|
|
|
Note that only parameter specification variables defined in global scope can
|
|
be pickled.
|
|
"""
|
|
|
|
# Trick Generic __parameters__.
|
|
__class__ = typing.TypeVar
|
|
|
|
@property
|
|
def args(self):
|
|
return ParamSpecArgs(self)
|
|
|
|
@property
|
|
def kwargs(self):
|
|
return ParamSpecKwargs(self)
|
|
|
|
def __init__(self, name, *, bound=None, covariant=False, contravariant=False,
|
|
default=None):
|
|
super().__init__([self])
|
|
self.__name__ = name
|
|
self.__covariant__ = bool(covariant)
|
|
self.__contravariant__ = bool(contravariant)
|
|
if bound:
|
|
self.__bound__ = typing._type_check(bound, 'Bound must be a type.')
|
|
else:
|
|
self.__bound__ = None
|
|
_DefaultMixin.__init__(self, default)
|
|
|
|
# for pickling:
|
|
try:
|
|
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
def_mod = None
|
|
if def_mod != 'typing_extensions':
|
|
self.__module__ = def_mod
|
|
|
|
def __repr__(self):
|
|
if self.__covariant__:
|
|
prefix = '+'
|
|
elif self.__contravariant__:
|
|
prefix = '-'
|
|
else:
|
|
prefix = '~'
|
|
return prefix + self.__name__
|
|
|
|
def __hash__(self):
|
|
return object.__hash__(self)
|
|
|
|
def __eq__(self, other):
|
|
return self is other
|
|
|
|
def __reduce__(self):
|
|
return self.__name__
|
|
|
|
# Hack to get typing._type_check to pass.
|
|
def __call__(self, *args, **kwargs):
|
|
pass
|
|
|
|
|
|
# 3.7-3.9
|
|
if not hasattr(typing, 'Concatenate'):
|
|
# Inherits from list as a workaround for Callable checks in Python < 3.9.2.
|
|
class _ConcatenateGenericAlias(list):
|
|
|
|
# Trick Generic into looking into this for __parameters__.
|
|
__class__ = typing._GenericAlias
|
|
|
|
# Flag in 3.8.
|
|
_special = False
|
|
|
|
def __init__(self, origin, args):
|
|
super().__init__(args)
|
|
self.__origin__ = origin
|
|
self.__args__ = args
|
|
|
|
def __repr__(self):
|
|
_type_repr = typing._type_repr
|
|
return (f'{_type_repr(self.__origin__)}'
|
|
f'[{", ".join(_type_repr(arg) for arg in self.__args__)}]')
|
|
|
|
def __hash__(self):
|
|
return hash((self.__origin__, self.__args__))
|
|
|
|
# Hack to get typing._type_check to pass in Generic.
|
|
def __call__(self, *args, **kwargs):
|
|
pass
|
|
|
|
@property
|
|
def __parameters__(self):
|
|
return tuple(
|
|
tp for tp in self.__args__ if isinstance(tp, (typing.TypeVar, ParamSpec))
|
|
)
|
|
|
|
|
|
# 3.7-3.9
|
|
@typing._tp_cache
|
|
def _concatenate_getitem(self, parameters):
|
|
if parameters == ():
|
|
raise TypeError("Cannot take a Concatenate of no types.")
|
|
if not isinstance(parameters, tuple):
|
|
parameters = (parameters,)
|
|
if not isinstance(parameters[-1], ParamSpec):
|
|
raise TypeError("The last parameter to Concatenate should be a "
|
|
"ParamSpec variable.")
|
|
msg = "Concatenate[arg, ...]: each arg must be a type."
|
|
parameters = tuple(typing._type_check(p, msg) for p in parameters)
|
|
return _ConcatenateGenericAlias(self, parameters)
|
|
|
|
|
|
# 3.10+
|
|
if hasattr(typing, 'Concatenate'):
|
|
Concatenate = typing.Concatenate
|
|
_ConcatenateGenericAlias = typing._ConcatenateGenericAlias # noqa
|
|
# 3.9
|
|
elif sys.version_info[:2] >= (3, 9):
|
|
@_TypeAliasForm
|
|
def Concatenate(self, parameters):
|
|
"""Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a
|
|
higher order function which adds, removes or transforms parameters of a
|
|
callable.
|
|
|
|
For example::
|
|
|
|
Callable[Concatenate[int, P], int]
|
|
|
|
See PEP 612 for detailed information.
|
|
"""
|
|
return _concatenate_getitem(self, parameters)
|
|
# 3.7-8
|
|
else:
|
|
class _ConcatenateForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
def __getitem__(self, parameters):
|
|
return _concatenate_getitem(self, parameters)
|
|
|
|
Concatenate = _ConcatenateForm(
|
|
'Concatenate',
|
|
doc="""Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a
|
|
higher order function which adds, removes or transforms parameters of a
|
|
callable.
|
|
|
|
For example::
|
|
|
|
Callable[Concatenate[int, P], int]
|
|
|
|
See PEP 612 for detailed information.
|
|
""")
|
|
|
|
# 3.10+
|
|
if hasattr(typing, 'TypeGuard'):
|
|
TypeGuard = typing.TypeGuard
|
|
# 3.9
|
|
elif sys.version_info[:2] >= (3, 9):
|
|
class _TypeGuardForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
@_TypeGuardForm
|
|
def TypeGuard(self, parameters):
|
|
"""Special typing form used to annotate the return type of a user-defined
|
|
type guard function. ``TypeGuard`` only accepts a single type argument.
|
|
At runtime, functions marked this way should return a boolean.
|
|
|
|
``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static
|
|
type checkers to determine a more precise type of an expression within a
|
|
program's code flow. Usually type narrowing is done by analyzing
|
|
conditional code flow and applying the narrowing to a block of code. The
|
|
conditional expression here is sometimes referred to as a "type guard".
|
|
|
|
Sometimes it would be convenient to use a user-defined boolean function
|
|
as a type guard. Such a function should use ``TypeGuard[...]`` as its
|
|
return type to alert static type checkers to this intention.
|
|
|
|
Using ``-> TypeGuard`` tells the static type checker that for a given
|
|
function:
|
|
|
|
1. The return value is a boolean.
|
|
2. If the return value is ``True``, the type of its argument
|
|
is the type inside ``TypeGuard``.
|
|
|
|
For example::
|
|
|
|
def is_str(val: Union[str, float]):
|
|
# "isinstance" type guard
|
|
if isinstance(val, str):
|
|
# Type of ``val`` is narrowed to ``str``
|
|
...
|
|
else:
|
|
# Else, type of ``val`` is narrowed to ``float``.
|
|
...
|
|
|
|
Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower
|
|
form of ``TypeA`` (it can even be a wider form) and this may lead to
|
|
type-unsafe results. The main reason is to allow for things like
|
|
narrowing ``List[object]`` to ``List[str]`` even though the latter is not
|
|
a subtype of the former, since ``List`` is invariant. The responsibility of
|
|
writing type-safe type guards is left to the user.
|
|
|
|
``TypeGuard`` also works with type variables. For more information, see
|
|
PEP 647 (User-Defined Type Guards).
|
|
"""
|
|
item = typing._type_check(parameters, f'{self} accepts only a single type.')
|
|
return typing._GenericAlias(self, (item,))
|
|
# 3.7-3.8
|
|
else:
|
|
class _TypeGuardForm(typing._SpecialForm, _root=True):
|
|
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
def __getitem__(self, parameters):
|
|
item = typing._type_check(parameters,
|
|
f'{self._name} accepts only a single type')
|
|
return typing._GenericAlias(self, (item,))
|
|
|
|
TypeGuard = _TypeGuardForm(
|
|
'TypeGuard',
|
|
doc="""Special typing form used to annotate the return type of a user-defined
|
|
type guard function. ``TypeGuard`` only accepts a single type argument.
|
|
At runtime, functions marked this way should return a boolean.
|
|
|
|
``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static
|
|
type checkers to determine a more precise type of an expression within a
|
|
program's code flow. Usually type narrowing is done by analyzing
|
|
conditional code flow and applying the narrowing to a block of code. The
|
|
conditional expression here is sometimes referred to as a "type guard".
|
|
|
|
Sometimes it would be convenient to use a user-defined boolean function
|
|
as a type guard. Such a function should use ``TypeGuard[...]`` as its
|
|
return type to alert static type checkers to this intention.
|
|
|
|
Using ``-> TypeGuard`` tells the static type checker that for a given
|
|
function:
|
|
|
|
1. The return value is a boolean.
|
|
2. If the return value is ``True``, the type of its argument
|
|
is the type inside ``TypeGuard``.
|
|
|
|
For example::
|
|
|
|
def is_str(val: Union[str, float]):
|
|
# "isinstance" type guard
|
|
if isinstance(val, str):
|
|
# Type of ``val`` is narrowed to ``str``
|
|
...
|
|
else:
|
|
# Else, type of ``val`` is narrowed to ``float``.
|
|
...
|
|
|
|
Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower
|
|
form of ``TypeA`` (it can even be a wider form) and this may lead to
|
|
type-unsafe results. The main reason is to allow for things like
|
|
narrowing ``List[object]`` to ``List[str]`` even though the latter is not
|
|
a subtype of the former, since ``List`` is invariant. The responsibility of
|
|
writing type-safe type guards is left to the user.
|
|
|
|
``TypeGuard`` also works with type variables. For more information, see
|
|
PEP 647 (User-Defined Type Guards).
|
|
""")
|
|
|
|
|
|
# Vendored from cpython typing._SpecialFrom
|
|
class _SpecialForm(typing._Final, _root=True):
|
|
__slots__ = ('_name', '__doc__', '_getitem')
|
|
|
|
def __init__(self, getitem):
|
|
self._getitem = getitem
|
|
self._name = getitem.__name__
|
|
self.__doc__ = getitem.__doc__
|
|
|
|
def __getattr__(self, item):
|
|
if item in {'__name__', '__qualname__'}:
|
|
return self._name
|
|
|
|
raise AttributeError(item)
|
|
|
|
def __mro_entries__(self, bases):
|
|
raise TypeError(f"Cannot subclass {self!r}")
|
|
|
|
def __repr__(self):
|
|
return f'typing_extensions.{self._name}'
|
|
|
|
def __reduce__(self):
|
|
return self._name
|
|
|
|
def __call__(self, *args, **kwds):
|
|
raise TypeError(f"Cannot instantiate {self!r}")
|
|
|
|
def __or__(self, other):
|
|
return typing.Union[self, other]
|
|
|
|
def __ror__(self, other):
|
|
return typing.Union[other, self]
|
|
|
|
def __instancecheck__(self, obj):
|
|
raise TypeError(f"{self} cannot be used with isinstance()")
|
|
|
|
def __subclasscheck__(self, cls):
|
|
raise TypeError(f"{self} cannot be used with issubclass()")
|
|
|
|
@typing._tp_cache
|
|
def __getitem__(self, parameters):
|
|
return self._getitem(self, parameters)
|
|
|
|
|
|
if hasattr(typing, "LiteralString"):
|
|
LiteralString = typing.LiteralString
|
|
else:
|
|
@_SpecialForm
|
|
def LiteralString(self, params):
|
|
"""Represents an arbitrary literal string.
|
|
|
|
Example::
|
|
|
|
from typing_extensions import LiteralString
|
|
|
|
def query(sql: LiteralString) -> ...:
|
|
...
|
|
|
|
query("SELECT * FROM table") # ok
|
|
query(f"SELECT * FROM {input()}") # not ok
|
|
|
|
See PEP 675 for details.
|
|
|
|
"""
|
|
raise TypeError(f"{self} is not subscriptable")
|
|
|
|
|
|
if hasattr(typing, "Self"):
|
|
Self = typing.Self
|
|
else:
|
|
@_SpecialForm
|
|
def Self(self, params):
|
|
"""Used to spell the type of "self" in classes.
|
|
|
|
Example::
|
|
|
|
from typing import Self
|
|
|
|
class ReturnsSelf:
|
|
def parse(self, data: bytes) -> Self:
|
|
...
|
|
return self
|
|
|
|
"""
|
|
|
|
raise TypeError(f"{self} is not subscriptable")
|
|
|
|
|
|
if hasattr(typing, "Never"):
|
|
Never = typing.Never
|
|
else:
|
|
@_SpecialForm
|
|
def Never(self, params):
|
|
"""The bottom type, a type that has no members.
|
|
|
|
This can be used to define a function that should never be
|
|
called, or a function that never returns::
|
|
|
|
from typing_extensions import Never
|
|
|
|
def never_call_me(arg: Never) -> None:
|
|
pass
|
|
|
|
def int_or_str(arg: int | str) -> None:
|
|
never_call_me(arg) # type checker error
|
|
match arg:
|
|
case int():
|
|
print("It's an int")
|
|
case str():
|
|
print("It's a str")
|
|
case _:
|
|
never_call_me(arg) # ok, arg is of type Never
|
|
|
|
"""
|
|
|
|
raise TypeError(f"{self} is not subscriptable")
|
|
|
|
|
|
if hasattr(typing, 'Required'):
|
|
Required = typing.Required
|
|
NotRequired = typing.NotRequired
|
|
elif sys.version_info[:2] >= (3, 9):
|
|
class _ExtensionsSpecialForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
@_ExtensionsSpecialForm
|
|
def Required(self, parameters):
|
|
"""A special typing construct to mark a key of a total=False TypedDict
|
|
as required. For example:
|
|
|
|
class Movie(TypedDict, total=False):
|
|
title: Required[str]
|
|
year: int
|
|
|
|
m = Movie(
|
|
title='The Matrix', # typechecker error if key is omitted
|
|
year=1999,
|
|
)
|
|
|
|
There is no runtime checking that a required key is actually provided
|
|
when instantiating a related TypedDict.
|
|
"""
|
|
item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
|
|
return typing._GenericAlias(self, (item,))
|
|
|
|
@_ExtensionsSpecialForm
|
|
def NotRequired(self, parameters):
|
|
"""A special typing construct to mark a key of a TypedDict as
|
|
potentially missing. For example:
|
|
|
|
class Movie(TypedDict):
|
|
title: str
|
|
year: NotRequired[int]
|
|
|
|
m = Movie(
|
|
title='The Matrix', # typechecker error if key is omitted
|
|
year=1999,
|
|
)
|
|
"""
|
|
item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
|
|
return typing._GenericAlias(self, (item,))
|
|
|
|
else:
|
|
class _RequiredForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
def __getitem__(self, parameters):
|
|
item = typing._type_check(parameters,
|
|
f'{self._name} accepts only a single type.')
|
|
return typing._GenericAlias(self, (item,))
|
|
|
|
Required = _RequiredForm(
|
|
'Required',
|
|
doc="""A special typing construct to mark a key of a total=False TypedDict
|
|
as required. For example:
|
|
|
|
class Movie(TypedDict, total=False):
|
|
title: Required[str]
|
|
year: int
|
|
|
|
m = Movie(
|
|
title='The Matrix', # typechecker error if key is omitted
|
|
year=1999,
|
|
)
|
|
|
|
There is no runtime checking that a required key is actually provided
|
|
when instantiating a related TypedDict.
|
|
""")
|
|
NotRequired = _RequiredForm(
|
|
'NotRequired',
|
|
doc="""A special typing construct to mark a key of a TypedDict as
|
|
potentially missing. For example:
|
|
|
|
class Movie(TypedDict):
|
|
title: str
|
|
year: NotRequired[int]
|
|
|
|
m = Movie(
|
|
title='The Matrix', # typechecker error if key is omitted
|
|
year=1999,
|
|
)
|
|
""")
|
|
|
|
|
|
if hasattr(typing, "Unpack"): # 3.11+
|
|
Unpack = typing.Unpack
|
|
elif sys.version_info[:2] >= (3, 9):
|
|
class _UnpackSpecialForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
class _UnpackAlias(typing._GenericAlias, _root=True):
|
|
__class__ = typing.TypeVar
|
|
|
|
@_UnpackSpecialForm
|
|
def Unpack(self, parameters):
|
|
"""A special typing construct to unpack a variadic type. For example:
|
|
|
|
Shape = TypeVarTuple('Shape')
|
|
Batch = NewType('Batch', int)
|
|
|
|
def add_batch_axis(
|
|
x: Array[Unpack[Shape]]
|
|
) -> Array[Batch, Unpack[Shape]]: ...
|
|
|
|
"""
|
|
item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
|
|
return _UnpackAlias(self, (item,))
|
|
|
|
def _is_unpack(obj):
|
|
return isinstance(obj, _UnpackAlias)
|
|
|
|
else:
|
|
class _UnpackAlias(typing._GenericAlias, _root=True):
|
|
__class__ = typing.TypeVar
|
|
|
|
class _UnpackForm(typing._SpecialForm, _root=True):
|
|
def __repr__(self):
|
|
return 'typing_extensions.' + self._name
|
|
|
|
def __getitem__(self, parameters):
|
|
item = typing._type_check(parameters,
|
|
f'{self._name} accepts only a single type.')
|
|
return _UnpackAlias(self, (item,))
|
|
|
|
Unpack = _UnpackForm(
|
|
'Unpack',
|
|
doc="""A special typing construct to unpack a variadic type. For example:
|
|
|
|
Shape = TypeVarTuple('Shape')
|
|
Batch = NewType('Batch', int)
|
|
|
|
def add_batch_axis(
|
|
x: Array[Unpack[Shape]]
|
|
) -> Array[Batch, Unpack[Shape]]: ...
|
|
|
|
""")
|
|
|
|
def _is_unpack(obj):
|
|
return isinstance(obj, _UnpackAlias)
|
|
|
|
|
|
if hasattr(typing, "TypeVarTuple"): # 3.11+
|
|
|
|
# Add default Parameter - PEP 696
|
|
class TypeVarTuple(typing.TypeVarTuple, _DefaultMixin, _root=True):
|
|
"""Type variable tuple."""
|
|
|
|
def __init__(self, name, *, default=None):
|
|
super().__init__(name)
|
|
_DefaultMixin.__init__(self, default)
|
|
|
|
# for pickling:
|
|
try:
|
|
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
def_mod = None
|
|
if def_mod != 'typing_extensions':
|
|
self.__module__ = def_mod
|
|
|
|
else:
|
|
class TypeVarTuple(_DefaultMixin):
|
|
"""Type variable tuple.
|
|
|
|
Usage::
|
|
|
|
Ts = TypeVarTuple('Ts')
|
|
|
|
In the same way that a normal type variable is a stand-in for a single
|
|
type such as ``int``, a type variable *tuple* is a stand-in for a *tuple*
|
|
type such as ``Tuple[int, str]``.
|
|
|
|
Type variable tuples can be used in ``Generic`` declarations.
|
|
Consider the following example::
|
|
|
|
class Array(Generic[*Ts]): ...
|
|
|
|
The ``Ts`` type variable tuple here behaves like ``tuple[T1, T2]``,
|
|
where ``T1`` and ``T2`` are type variables. To use these type variables
|
|
as type parameters of ``Array``, we must *unpack* the type variable tuple using
|
|
the star operator: ``*Ts``. The signature of ``Array`` then behaves
|
|
as if we had simply written ``class Array(Generic[T1, T2]): ...``.
|
|
In contrast to ``Generic[T1, T2]``, however, ``Generic[*Shape]`` allows
|
|
us to parameterise the class with an *arbitrary* number of type parameters.
|
|
|
|
Type variable tuples can be used anywhere a normal ``TypeVar`` can.
|
|
This includes class definitions, as shown above, as well as function
|
|
signatures and variable annotations::
|
|
|
|
class Array(Generic[*Ts]):
|
|
|
|
def __init__(self, shape: Tuple[*Ts]):
|
|
self._shape: Tuple[*Ts] = shape
|
|
|
|
def get_shape(self) -> Tuple[*Ts]:
|
|
return self._shape
|
|
|
|
shape = (Height(480), Width(640))
|
|
x: Array[Height, Width] = Array(shape)
|
|
y = abs(x) # Inferred type is Array[Height, Width]
|
|
z = x + x # ... is Array[Height, Width]
|
|
x.get_shape() # ... is tuple[Height, Width]
|
|
|
|
"""
|
|
|
|
# Trick Generic __parameters__.
|
|
__class__ = typing.TypeVar
|
|
|
|
def __iter__(self):
|
|
yield self.__unpacked__
|
|
|
|
def __init__(self, name, *, default=None):
|
|
self.__name__ = name
|
|
_DefaultMixin.__init__(self, default)
|
|
|
|
# for pickling:
|
|
try:
|
|
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
|
|
except (AttributeError, ValueError):
|
|
def_mod = None
|
|
if def_mod != 'typing_extensions':
|
|
self.__module__ = def_mod
|
|
|
|
self.__unpacked__ = Unpack[self]
|
|
|
|
def __repr__(self):
|
|
return self.__name__
|
|
|
|
def __hash__(self):
|
|
return object.__hash__(self)
|
|
|
|
def __eq__(self, other):
|
|
return self is other
|
|
|
|
def __reduce__(self):
|
|
return self.__name__
|
|
|
|
def __init_subclass__(self, *args, **kwds):
|
|
if '_root' not in kwds:
|
|
raise TypeError("Cannot subclass special typing classes")
|
|
|
|
|
|
if hasattr(typing, "reveal_type"):
|
|
reveal_type = typing.reveal_type
|
|
else:
|
|
def reveal_type(__obj: T) -> T:
|
|
"""Reveal the inferred type of a variable.
|
|
|
|
When a static type checker encounters a call to ``reveal_type()``,
|
|
it will emit the inferred type of the argument::
|
|
|
|
x: int = 1
|
|
reveal_type(x)
|
|
|
|
Running a static type checker (e.g., ``mypy``) on this example
|
|
will produce output similar to 'Revealed type is "builtins.int"'.
|
|
|
|
At runtime, the function prints the runtime type of the
|
|
argument and returns it unchanged.
|
|
|
|
"""
|
|
print(f"Runtime type is {type(__obj).__name__!r}", file=sys.stderr)
|
|
return __obj
|
|
|
|
|
|
if hasattr(typing, "assert_never"):
|
|
assert_never = typing.assert_never
|
|
else:
|
|
def assert_never(__arg: Never) -> Never:
|
|
"""Assert to the type checker that a line of code is unreachable.
|
|
|
|
Example::
|
|
|
|
def int_or_str(arg: int | str) -> None:
|
|
match arg:
|
|
case int():
|
|
print("It's an int")
|
|
case str():
|
|
print("It's a str")
|
|
case _:
|
|
assert_never(arg)
|
|
|
|
If a type checker finds that a call to assert_never() is
|
|
reachable, it will emit an error.
|
|
|
|
At runtime, this throws an exception when called.
|
|
|
|
"""
|
|
raise AssertionError("Expected code to be unreachable")
|
|
|
|
|
|
if hasattr(typing, 'dataclass_transform'):
|
|
dataclass_transform = typing.dataclass_transform
|
|
else:
|
|
def dataclass_transform(
|
|
*,
|
|
eq_default: bool = True,
|
|
order_default: bool = False,
|
|
kw_only_default: bool = False,
|
|
field_specifiers: typing.Tuple[
|
|
typing.Union[typing.Type[typing.Any], typing.Callable[..., typing.Any]],
|
|
...
|
|
] = (),
|
|
**kwargs: typing.Any,
|
|
) -> typing.Callable[[T], T]:
|
|
"""Decorator that marks a function, class, or metaclass as providing
|
|
dataclass-like behavior.
|
|
|
|
Example:
|
|
|
|
from typing_extensions import dataclass_transform
|
|
|
|
_T = TypeVar("_T")
|
|
|
|
# Used on a decorator function
|
|
@dataclass_transform()
|
|
def create_model(cls: type[_T]) -> type[_T]:
|
|
...
|
|
return cls
|
|
|
|
@create_model
|
|
class CustomerModel:
|
|
id: int
|
|
name: str
|
|
|
|
# Used on a base class
|
|
@dataclass_transform()
|
|
class ModelBase: ...
|
|
|
|
class CustomerModel(ModelBase):
|
|
id: int
|
|
name: str
|
|
|
|
# Used on a metaclass
|
|
@dataclass_transform()
|
|
class ModelMeta(type): ...
|
|
|
|
class ModelBase(metaclass=ModelMeta): ...
|
|
|
|
class CustomerModel(ModelBase):
|
|
id: int
|
|
name: str
|
|
|
|
Each of the ``CustomerModel`` classes defined in this example will now
|
|
behave similarly to a dataclass created with the ``@dataclasses.dataclass``
|
|
decorator. For example, the type checker will synthesize an ``__init__``
|
|
method.
|
|
|
|
The arguments to this decorator can be used to customize this behavior:
|
|
- ``eq_default`` indicates whether the ``eq`` parameter is assumed to be
|
|
True or False if it is omitted by the caller.
|
|
- ``order_default`` indicates whether the ``order`` parameter is
|
|
assumed to be True or False if it is omitted by the caller.
|
|
- ``kw_only_default`` indicates whether the ``kw_only`` parameter is
|
|
assumed to be True or False if it is omitted by the caller.
|
|
- ``field_specifiers`` specifies a static list of supported classes
|
|
or functions that describe fields, similar to ``dataclasses.field()``.
|
|
|
|
At runtime, this decorator records its arguments in the
|
|
``__dataclass_transform__`` attribute on the decorated object.
|
|
|
|
See PEP 681 for details.
|
|
|
|
"""
|
|
def decorator(cls_or_fn):
|
|
cls_or_fn.__dataclass_transform__ = {
|
|
"eq_default": eq_default,
|
|
"order_default": order_default,
|
|
"kw_only_default": kw_only_default,
|
|
"field_specifiers": field_specifiers,
|
|
"kwargs": kwargs,
|
|
}
|
|
return cls_or_fn
|
|
return decorator
|
|
|
|
|
|
if hasattr(typing, "override"):
|
|
override = typing.override
|
|
else:
|
|
_F = typing.TypeVar("_F", bound=typing.Callable[..., typing.Any])
|
|
|
|
def override(__arg: _F) -> _F:
|
|
"""Indicate that a method is intended to override a method in a base class.
|
|
|
|
Usage:
|
|
|
|
class Base:
|
|
def method(self) -> None: ...
|
|
pass
|
|
|
|
class Child(Base):
|
|
@override
|
|
def method(self) -> None:
|
|
super().method()
|
|
|
|
When this decorator is applied to a method, the type checker will
|
|
validate that it overrides a method with the same name on a base class.
|
|
This helps prevent bugs that may occur when a base class is changed
|
|
without an equivalent change to a child class.
|
|
|
|
See PEP 698 for details.
|
|
|
|
"""
|
|
return __arg
|
|
|
|
|
|
# We have to do some monkey patching to deal with the dual nature of
|
|
# Unpack/TypeVarTuple:
|
|
# - We want Unpack to be a kind of TypeVar so it gets accepted in
|
|
# Generic[Unpack[Ts]]
|
|
# - We want it to *not* be treated as a TypeVar for the purposes of
|
|
# counting generic parameters, so that when we subscript a generic,
|
|
# the runtime doesn't try to substitute the Unpack with the subscripted type.
|
|
if not hasattr(typing, "TypeVarTuple"):
|
|
typing._collect_type_vars = _collect_type_vars
|
|
typing._check_generic = _check_generic
|
|
|
|
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# Backport typing.NamedTuple as it exists in Python 3.11.
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# In 3.11, the ability to define generic `NamedTuple`s was supported.
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# This was explicitly disallowed in 3.9-3.10, and only half-worked in <=3.8.
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if sys.version_info >= (3, 11):
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NamedTuple = typing.NamedTuple
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else:
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def _caller():
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try:
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return sys._getframe(2).f_globals.get('__name__', '__main__')
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except (AttributeError, ValueError): # For platforms without _getframe()
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return None
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def _make_nmtuple(name, types, module, defaults=()):
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fields = [n for n, t in types]
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annotations = {n: typing._type_check(t, f"field {n} annotation must be a type")
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for n, t in types}
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nm_tpl = collections.namedtuple(name, fields,
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defaults=defaults, module=module)
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nm_tpl.__annotations__ = nm_tpl.__new__.__annotations__ = annotations
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# The `_field_types` attribute was removed in 3.9;
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# in earlier versions, it is the same as the `__annotations__` attribute
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if sys.version_info < (3, 9):
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nm_tpl._field_types = annotations
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return nm_tpl
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_prohibited_namedtuple_fields = typing._prohibited
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_special_namedtuple_fields = frozenset({'__module__', '__name__', '__annotations__'})
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class _NamedTupleMeta(type):
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def __new__(cls, typename, bases, ns):
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assert _NamedTuple in bases
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for base in bases:
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if base is not _NamedTuple and base is not typing.Generic:
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raise TypeError(
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'can only inherit from a NamedTuple type and Generic')
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bases = tuple(tuple if base is _NamedTuple else base for base in bases)
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types = ns.get('__annotations__', {})
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default_names = []
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for field_name in types:
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if field_name in ns:
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default_names.append(field_name)
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elif default_names:
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raise TypeError(f"Non-default namedtuple field {field_name} "
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f"cannot follow default field"
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f"{'s' if len(default_names) > 1 else ''} "
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f"{', '.join(default_names)}")
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nm_tpl = _make_nmtuple(
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typename, types.items(),
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defaults=[ns[n] for n in default_names],
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module=ns['__module__']
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)
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nm_tpl.__bases__ = bases
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if typing.Generic in bases:
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class_getitem = typing.Generic.__class_getitem__.__func__
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nm_tpl.__class_getitem__ = classmethod(class_getitem)
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# update from user namespace without overriding special namedtuple attributes
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for key in ns:
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if key in _prohibited_namedtuple_fields:
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raise AttributeError("Cannot overwrite NamedTuple attribute " + key)
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elif key not in _special_namedtuple_fields and key not in nm_tpl._fields:
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setattr(nm_tpl, key, ns[key])
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if typing.Generic in bases:
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nm_tpl.__init_subclass__()
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return nm_tpl
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def NamedTuple(__typename, __fields=None, **kwargs):
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if __fields is None:
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__fields = kwargs.items()
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elif kwargs:
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raise TypeError("Either list of fields or keywords"
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" can be provided to NamedTuple, not both")
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return _make_nmtuple(__typename, __fields, module=_caller())
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NamedTuple.__doc__ = typing.NamedTuple.__doc__
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_NamedTuple = type.__new__(_NamedTupleMeta, 'NamedTuple', (), {})
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# On 3.8+, alter the signature so that it matches typing.NamedTuple.
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# The signature of typing.NamedTuple on >=3.8 is invalid syntax in Python 3.7,
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# so just leave the signature as it is on 3.7.
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if sys.version_info >= (3, 8):
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NamedTuple.__text_signature__ = '(typename, fields=None, /, **kwargs)'
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def _namedtuple_mro_entries(bases):
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assert NamedTuple in bases
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return (_NamedTuple,)
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NamedTuple.__mro_entries__ = _namedtuple_mro_entries
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