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Enso-Bot/venv/Lib/site-packages/typing_extensions.py

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import abc
import collections
import contextlib
import sys
import typing
import collections.abc as collections_abc
import operator
# These are used by Protocol implementation
# We use internal typing helpers here, but this significantly reduces
# code duplication. (Also this is only until Protocol is in typing.)
from typing import Generic, Callable, TypeVar, Tuple
# After PEP 560, internal typing API was substantially reworked.
# This is especially important for Protocol class which uses internal APIs
# quite extensivelly.
PEP_560 = sys.version_info[:3] >= (3, 7, 0)
if PEP_560:
GenericMeta = TypingMeta = type
else:
from typing import GenericMeta, TypingMeta
OLD_GENERICS = False
try:
from typing import _type_vars, _next_in_mro, _type_check
except ImportError:
OLD_GENERICS = True
try:
from typing import _subs_tree # noqa
SUBS_TREE = True
except ImportError:
SUBS_TREE = False
try:
from typing import _tp_cache
except ImportError:
def _tp_cache(x):
return x
try:
from typing import _TypingEllipsis, _TypingEmpty
except ImportError:
class _TypingEllipsis:
pass
class _TypingEmpty:
pass
# The two functions below are copies of typing internal helpers.
# They are needed by _ProtocolMeta
def _no_slots_copy(dct):
dict_copy = dict(dct)
if '__slots__' in dict_copy:
for slot in dict_copy['__slots__']:
dict_copy.pop(slot, None)
return dict_copy
def _check_generic(cls, parameters):
if not cls.__parameters__:
raise TypeError("%s is not a generic class" % repr(cls))
alen = len(parameters)
elen = len(cls.__parameters__)
if alen != elen:
raise TypeError("Too %s parameters for %s; actual %s, expected %s" %
("many" if alen > elen else "few", repr(cls), alen, elen))
if hasattr(typing, '_generic_new'):
_generic_new = typing._generic_new
else:
# Note: The '_generic_new(...)' function is used as a part of the
# process of creating a generic type and was added to the typing module
# as of Python 3.5.3.
#
# We've defined '_generic_new(...)' below to exactly match the behavior
# implemented in older versions of 'typing' bundled with Python 3.5.0 to
# 3.5.2. This helps eliminate redundancy when defining collection types
# like 'Deque' later.
#
# See https://github.com/python/typing/pull/308 for more details -- in
# particular, compare and contrast the definition of types like
# 'typing.List' before and after the merge.
def _generic_new(base_cls, cls, *args, **kwargs):
return base_cls.__new__(cls, *args, **kwargs)
# See https://github.com/python/typing/pull/439
if hasattr(typing, '_geqv'):
from typing import _geqv
_geqv_defined = True
else:
_geqv = None
_geqv_defined = False
if sys.version_info[:2] >= (3, 6):
import _collections_abc
_check_methods_in_mro = _collections_abc._check_methods
else:
def _check_methods_in_mro(C, *methods):
mro = C.__mro__
for method in methods:
for B in mro:
if method in B.__dict__:
if B.__dict__[method] is None:
return NotImplemented
break
else:
return NotImplemented
return True
# Please keep __all__ alphabetized within each category.
__all__ = [
# Super-special typing primitives.
'ClassVar',
'Final',
'Type',
# ABCs (from collections.abc).
# The following are added depending on presence
# of their non-generic counterparts in stdlib:
# 'Awaitable',
# 'AsyncIterator',
# 'AsyncIterable',
# 'Coroutine',
# 'AsyncGenerator',
# 'AsyncContextManager',
# 'ChainMap',
# Concrete collection types.
'ContextManager',
'Counter',
'Deque',
'DefaultDict',
'TypedDict',
# One-off things.
'final',
'IntVar',
'Literal',
'NewType',
'overload',
'Text',
'TYPE_CHECKING',
]
# Annotated relies on substitution trees of pep 560. It will not work for
# versions of typing older than 3.5.3
HAVE_ANNOTATED = PEP_560 or SUBS_TREE
if PEP_560:
__all__.extend(["get_args", "get_origin", "get_type_hints"])
if HAVE_ANNOTATED:
__all__.append("Annotated")
# Protocols are hard to backport to the original version of typing 3.5.0
HAVE_PROTOCOLS = sys.version_info[:3] != (3, 5, 0)
if HAVE_PROTOCOLS:
__all__.extend(['Protocol', 'runtime', 'runtime_checkable'])
# TODO
if hasattr(typing, 'NoReturn'):
NoReturn = typing.NoReturn
elif hasattr(typing, '_FinalTypingBase'):
class _NoReturn(typing._FinalTypingBase, _root=True):
"""Special type indicating functions that never return.
Example::
from typing import NoReturn
def stop() -> NoReturn:
raise Exception('no way')
This type is invalid in other positions, e.g., ``List[NoReturn]``
will fail in static type checkers.
"""
__slots__ = ()
def __instancecheck__(self, obj):
raise TypeError("NoReturn cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("NoReturn cannot be used with issubclass().")
NoReturn = _NoReturn(_root=True)
else:
class _NoReturnMeta(typing.TypingMeta):
"""Metaclass for NoReturn"""
def __new__(cls, name, bases, namespace, _root=False):
return super().__new__(cls, name, bases, namespace, _root=_root)
def __instancecheck__(self, obj):
raise TypeError("NoReturn cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("NoReturn cannot be used with issubclass().")
class NoReturn(typing.Final, metaclass=_NoReturnMeta, _root=True):
"""Special type indicating functions that never return.
Example::
from typing import NoReturn
def stop() -> NoReturn:
raise Exception('no way')
This type is invalid in other positions, e.g., ``List[NoReturn]``
will fail in static type checkers.
"""
__slots__ = ()
# Some unconstrained type variables. These are used by the container types.
# (These are not for export.)
T = typing.TypeVar('T') # Any type.
KT = typing.TypeVar('KT') # Key type.
VT = typing.TypeVar('VT') # Value type.
T_co = typing.TypeVar('T_co', covariant=True) # Any type covariant containers.
V_co = typing.TypeVar('V_co', covariant=True) # Any type covariant containers.
VT_co = typing.TypeVar('VT_co', covariant=True) # Value type covariant containers.
T_contra = typing.TypeVar('T_contra', contravariant=True) # Ditto contravariant.
if hasattr(typing, 'ClassVar'):
ClassVar = typing.ClassVar
elif hasattr(typing, '_FinalTypingBase'):
class _ClassVar(typing._FinalTypingBase, _root=True):
"""Special type construct to mark class variables.
An annotation wrapped in ClassVar indicates that a given
attribute is intended to be used as a class variable and
should not be set on instances of that class. Usage::
class Starship:
stats: ClassVar[Dict[str, int]] = {} # class variable
damage: int = 10 # instance variable
ClassVar accepts only types and cannot be further subscribed.
Note that ClassVar is not a class itself, and should not
be used with isinstance() or issubclass().
"""
__slots__ = ('__type__',)
def __init__(self, tp=None, **kwds):
self.__type__ = tp
def __getitem__(self, item):
cls = type(self)
if self.__type__ is None:
return cls(typing._type_check(item,
'{} accepts only single type.'.format(cls.__name__[1:])),
_root=True)
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
def _eval_type(self, globalns, localns):
new_tp = typing._eval_type(self.__type__, globalns, localns)
if new_tp == self.__type__:
return self
return type(self)(new_tp, _root=True)
def __repr__(self):
r = super().__repr__()
if self.__type__ is not None:
r += '[{}]'.format(typing._type_repr(self.__type__))
return r
def __hash__(self):
return hash((type(self).__name__, self.__type__))
def __eq__(self, other):
if not isinstance(other, _ClassVar):
return NotImplemented
if self.__type__ is not None:
return self.__type__ == other.__type__
return self is other
ClassVar = _ClassVar(_root=True)
else:
class _ClassVarMeta(typing.TypingMeta):
"""Metaclass for ClassVar"""
def __new__(cls, name, bases, namespace, tp=None, _root=False):
self = super().__new__(cls, name, bases, namespace, _root=_root)
if tp is not None:
self.__type__ = tp
return self
def __instancecheck__(self, obj):
raise TypeError("ClassVar cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("ClassVar cannot be used with issubclass().")
def __getitem__(self, item):
cls = type(self)
if self.__type__ is not None:
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
param = typing._type_check(
item,
'{} accepts only single type.'.format(cls.__name__[1:]))
return cls(self.__name__, self.__bases__,
dict(self.__dict__), tp=param, _root=True)
def _eval_type(self, globalns, localns):
new_tp = typing._eval_type(self.__type__, globalns, localns)
if new_tp == self.__type__:
return self
return type(self)(self.__name__, self.__bases__,
dict(self.__dict__), tp=self.__type__,
_root=True)
def __repr__(self):
r = super().__repr__()
if self.__type__ is not None:
r += '[{}]'.format(typing._type_repr(self.__type__))
return r
def __hash__(self):
return hash((type(self).__name__, self.__type__))
def __eq__(self, other):
if not isinstance(other, ClassVar):
return NotImplemented
if self.__type__ is not None:
return self.__type__ == other.__type__
return self is other
class ClassVar(typing.Final, metaclass=_ClassVarMeta, _root=True):
"""Special type construct to mark class variables.
An annotation wrapped in ClassVar indicates that a given
attribute is intended to be used as a class variable and
should not be set on instances of that class. Usage::
class Starship:
stats: ClassVar[Dict[str, int]] = {} # class variable
damage: int = 10 # instance variable
ClassVar accepts only types and cannot be further subscribed.
Note that ClassVar is not a class itself, and should not
be used with isinstance() or issubclass().
"""
__type__ = None
# On older versions of typing there is an internal class named "Final".
if hasattr(typing, 'Final') and sys.version_info[:2] >= (3, 7):
Final = typing.Final
elif sys.version_info[:2] >= (3, 7):
class _FinalForm(typing._SpecialForm, _root=True):
def __repr__(self):
return 'typing_extensions.' + self._name
def __getitem__(self, parameters):
item = typing._type_check(parameters,
'{} accepts only single type'.format(self._name))
return _GenericAlias(self, (item,))
Final = _FinalForm('Final',
doc="""A special typing construct to indicate that a name
cannot be re-assigned or overridden in a subclass.
For example:
MAX_SIZE: Final = 9000
MAX_SIZE += 1 # Error reported by type checker
class Connection:
TIMEOUT: Final[int] = 10
class FastConnector(Connection):
TIMEOUT = 1 # Error reported by type checker
There is no runtime checking of these properties.""")
elif hasattr(typing, '_FinalTypingBase'):
class _Final(typing._FinalTypingBase, _root=True):
"""A special typing construct to indicate that a name
cannot be re-assigned or overridden in a subclass.
For example:
MAX_SIZE: Final = 9000
MAX_SIZE += 1 # Error reported by type checker
class Connection:
TIMEOUT: Final[int] = 10
class FastConnector(Connection):
TIMEOUT = 1 # Error reported by type checker
There is no runtime checking of these properties.
"""
__slots__ = ('__type__',)
def __init__(self, tp=None, **kwds):
self.__type__ = tp
def __getitem__(self, item):
cls = type(self)
if self.__type__ is None:
return cls(typing._type_check(item,
'{} accepts only single type.'.format(cls.__name__[1:])),
_root=True)
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
def _eval_type(self, globalns, localns):
new_tp = typing._eval_type(self.__type__, globalns, localns)
if new_tp == self.__type__:
return self
return type(self)(new_tp, _root=True)
def __repr__(self):
r = super().__repr__()
if self.__type__ is not None:
r += '[{}]'.format(typing._type_repr(self.__type__))
return r
def __hash__(self):
return hash((type(self).__name__, self.__type__))
def __eq__(self, other):
if not isinstance(other, _Final):
return NotImplemented
if self.__type__ is not None:
return self.__type__ == other.__type__
return self is other
Final = _Final(_root=True)
else:
class _FinalMeta(typing.TypingMeta):
"""Metaclass for Final"""
def __new__(cls, name, bases, namespace, tp=None, _root=False):
self = super().__new__(cls, name, bases, namespace, _root=_root)
if tp is not None:
self.__type__ = tp
return self
def __instancecheck__(self, obj):
raise TypeError("Final cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("Final cannot be used with issubclass().")
def __getitem__(self, item):
cls = type(self)
if self.__type__ is not None:
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
param = typing._type_check(
item,
'{} accepts only single type.'.format(cls.__name__[1:]))
return cls(self.__name__, self.__bases__,
dict(self.__dict__), tp=param, _root=True)
def _eval_type(self, globalns, localns):
new_tp = typing._eval_type(self.__type__, globalns, localns)
if new_tp == self.__type__:
return self
return type(self)(self.__name__, self.__bases__,
dict(self.__dict__), tp=self.__type__,
_root=True)
def __repr__(self):
r = super().__repr__()
if self.__type__ is not None:
r += '[{}]'.format(typing._type_repr(self.__type__))
return r
def __hash__(self):
return hash((type(self).__name__, self.__type__))
def __eq__(self, other):
if not isinstance(other, Final):
return NotImplemented
if self.__type__ is not None:
return self.__type__ == other.__type__
return self is other
class Final(typing.Final, metaclass=_FinalMeta, _root=True):
"""A special typing construct to indicate that a name
cannot be re-assigned or overridden in a subclass.
For example:
MAX_SIZE: Final = 9000
MAX_SIZE += 1 # Error reported by type checker
class Connection:
TIMEOUT: Final[int] = 10
class FastConnector(Connection):
TIMEOUT = 1 # Error reported by type checker
There is no runtime checking of these properties.
"""
__type__ = None
if hasattr(typing, 'final'):
final = typing.final
else:
def final(f):
"""This decorator can be used to indicate to type checkers that
the decorated method cannot be overridden, and decorated class
cannot be subclassed. For example:
class Base:
@final
def done(self) -> None:
...
class Sub(Base):
def done(self) -> None: # Error reported by type checker
...
@final
class Leaf:
...
class Other(Leaf): # Error reported by type checker
...
There is no runtime checking of these properties.
"""
return f
def IntVar(name):
return TypeVar(name)
if hasattr(typing, 'Literal'):
Literal = typing.Literal
elif sys.version_info[:2] >= (3, 7):
class _LiteralForm(typing._SpecialForm, _root=True):
def __repr__(self):
return 'typing_extensions.' + self._name
def __getitem__(self, parameters):
return _GenericAlias(self, parameters)
Literal = _LiteralForm('Literal',
doc="""A type that can be used to indicate to type checkers
that the corresponding value has a value literally equivalent
to the provided parameter. For example:
var: Literal[4] = 4
The type checker understands that 'var' is literally equal to
the value 4 and no other value.
Literal[...] cannot be subclassed. There is no runtime
checking verifying that the parameter is actually a value
instead of a type.""")
elif hasattr(typing, '_FinalTypingBase'):
class _Literal(typing._FinalTypingBase, _root=True):
"""A type that can be used to indicate to type checkers that the
corresponding value has a value literally equivalent to the
provided parameter. For example:
var: Literal[4] = 4
The type checker understands that 'var' is literally equal to the
value 4 and no other value.
Literal[...] cannot be subclassed. There is no runtime checking
verifying that the parameter is actually a value instead of a type.
"""
__slots__ = ('__values__',)
def __init__(self, values=None, **kwds):
self.__values__ = values
def __getitem__(self, values):
cls = type(self)
if self.__values__ is None:
if not isinstance(values, tuple):
values = (values,)
return cls(values, _root=True)
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
def _eval_type(self, globalns, localns):
return self
def __repr__(self):
r = super().__repr__()
if self.__values__ is not None:
r += '[{}]'.format(', '.join(map(typing._type_repr, self.__values__)))
return r
def __hash__(self):
return hash((type(self).__name__, self.__values__))
def __eq__(self, other):
if not isinstance(other, _Literal):
return NotImplemented
if self.__values__ is not None:
return self.__values__ == other.__values__
return self is other
Literal = _Literal(_root=True)
else:
class _LiteralMeta(typing.TypingMeta):
"""Metaclass for Literal"""
def __new__(cls, name, bases, namespace, values=None, _root=False):
self = super().__new__(cls, name, bases, namespace, _root=_root)
if values is not None:
self.__values__ = values
return self
def __instancecheck__(self, obj):
raise TypeError("Literal cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("Literal cannot be used with issubclass().")
def __getitem__(self, item):
cls = type(self)
if self.__values__ is not None:
raise TypeError('{} cannot be further subscripted'
.format(cls.__name__[1:]))
if not isinstance(item, tuple):
item = (item,)
return cls(self.__name__, self.__bases__,
dict(self.__dict__), values=item, _root=True)
def _eval_type(self, globalns, localns):
return self
def __repr__(self):
r = super().__repr__()
if self.__values__ is not None:
r += '[{}]'.format(', '.join(map(typing._type_repr, self.__values__)))
return r
def __hash__(self):
return hash((type(self).__name__, self.__values__))
def __eq__(self, other):
if not isinstance(other, Literal):
return NotImplemented
if self.__values__ is not None:
return self.__values__ == other.__values__
return self is other
class Literal(typing.Final, metaclass=_LiteralMeta, _root=True):
"""A type that can be used to indicate to type checkers that the
corresponding value has a value literally equivalent to the
provided parameter. For example:
var: Literal[4] = 4
The type checker understands that 'var' is literally equal to the
value 4 and no other value.
Literal[...] cannot be subclassed. There is no runtime checking
verifying that the parameter is actually a value instead of a type.
"""
__values__ = None
def _overload_dummy(*args, **kwds):
"""Helper for @overload to raise when called."""
raise NotImplementedError(
"You should not call an overloaded function. "
"A series of @overload-decorated functions "
"outside a stub module should always be followed "
"by an implementation that is not @overload-ed.")
def overload(func):
"""Decorator for overloaded functions/methods.
In a stub file, place two or more stub definitions for the same
function in a row, each decorated with @overload. For example:
@overload
def utf8(value: None) -> None: ...
@overload
def utf8(value: bytes) -> bytes: ...
@overload
def utf8(value: str) -> bytes: ...
In a non-stub file (i.e. a regular .py file), do the same but
follow it with an implementation. The implementation should *not*
be decorated with @overload. For example:
@overload
def utf8(value: None) -> None: ...
@overload
def utf8(value: bytes) -> bytes: ...
@overload
def utf8(value: str) -> bytes: ...
def utf8(value):
# implementation goes here
"""
return _overload_dummy
# This is not a real generic class. Don't use outside annotations.
if hasattr(typing, 'Type'):
Type = typing.Type
else:
# Internal type variable used for Type[].
CT_co = typing.TypeVar('CT_co', covariant=True, bound=type)
class Type(typing.Generic[CT_co], extra=type):
"""A special construct usable to annotate class objects.
For example, suppose we have the following classes::
class User: ... # Abstract base for User classes
class BasicUser(User): ...
class ProUser(User): ...
class TeamUser(User): ...
And a function that takes a class argument that's a subclass of
User and returns an instance of the corresponding class::
U = TypeVar('U', bound=User)
def new_user(user_class: Type[U]) -> U:
user = user_class()
# (Here we could write the user object to a database)
return user
joe = new_user(BasicUser)
At this point the type checker knows that joe has type BasicUser.
"""
__slots__ = ()
# Various ABCs mimicking those in collections.abc.
# A few are simply re-exported for completeness.
def _define_guard(type_name):
"""
Returns True if the given type isn't defined in typing but
is defined in collections_abc.
Adds the type to __all__ if the collection is found in either
typing or collection_abc.
"""
if hasattr(typing, type_name):
__all__.append(type_name)
globals()[type_name] = getattr(typing, type_name)
return False
elif hasattr(collections_abc, type_name):
__all__.append(type_name)
return True
else:
return False
class _ExtensionsGenericMeta(GenericMeta):
def __subclasscheck__(self, subclass):
"""This mimics a more modern GenericMeta.__subclasscheck__() logic
(that does not have problems with recursion) to work around interactions
between collections, typing, and typing_extensions on older
versions of Python, see https://github.com/python/typing/issues/501.
"""
if sys.version_info[:3] >= (3, 5, 3) or sys.version_info[:3] < (3, 5, 0):
if self.__origin__ is not None:
if sys._getframe(1).f_globals['__name__'] not in ['abc', 'functools']:
raise TypeError("Parameterized generics cannot be used with class "
"or instance checks")
return False
if not self.__extra__:
return super().__subclasscheck__(subclass)
res = self.__extra__.__subclasshook__(subclass)
if res is not NotImplemented:
return res
if self.__extra__ in subclass.__mro__:
return True
for scls in self.__extra__.__subclasses__():
if isinstance(scls, GenericMeta):
continue
if issubclass(subclass, scls):
return True
return False
if _define_guard('Awaitable'):
class Awaitable(typing.Generic[T_co], metaclass=_ExtensionsGenericMeta,
extra=collections_abc.Awaitable):
__slots__ = ()
if _define_guard('Coroutine'):
class Coroutine(Awaitable[V_co], typing.Generic[T_co, T_contra, V_co],
metaclass=_ExtensionsGenericMeta,
extra=collections_abc.Coroutine):
__slots__ = ()
if _define_guard('AsyncIterable'):
class AsyncIterable(typing.Generic[T_co],
metaclass=_ExtensionsGenericMeta,
extra=collections_abc.AsyncIterable):
__slots__ = ()
if _define_guard('AsyncIterator'):
class AsyncIterator(AsyncIterable[T_co],
metaclass=_ExtensionsGenericMeta,
extra=collections_abc.AsyncIterator):
__slots__ = ()
if hasattr(typing, 'Deque'):
Deque = typing.Deque
elif _geqv_defined:
class Deque(collections.deque, typing.MutableSequence[T],
metaclass=_ExtensionsGenericMeta,
extra=collections.deque):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, Deque):
return collections.deque(*args, **kwds)
return _generic_new(collections.deque, cls, *args, **kwds)
else:
class Deque(collections.deque, typing.MutableSequence[T],
metaclass=_ExtensionsGenericMeta,
extra=collections.deque):
__slots__ = ()
def __new__(cls, *args, **kwds):
if cls._gorg is Deque:
return collections.deque(*args, **kwds)
return _generic_new(collections.deque, cls, *args, **kwds)
if hasattr(typing, 'ContextManager'):
ContextManager = typing.ContextManager
elif hasattr(contextlib, 'AbstractContextManager'):
class ContextManager(typing.Generic[T_co],
metaclass=_ExtensionsGenericMeta,
extra=contextlib.AbstractContextManager):
__slots__ = ()
else:
class ContextManager(typing.Generic[T_co]):
__slots__ = ()
def __enter__(self):
return self
@abc.abstractmethod
def __exit__(self, exc_type, exc_value, traceback):
return None
@classmethod
def __subclasshook__(cls, C):
if cls is ContextManager:
# In Python 3.6+, it is possible to set a method to None to
# explicitly indicate that the class does not implement an ABC
# (https://bugs.python.org/issue25958), but we do not support
# that pattern here because this fallback class is only used
# in Python 3.5 and earlier.
if (any("__enter__" in B.__dict__ for B in C.__mro__) and
any("__exit__" in B.__dict__ for B in C.__mro__)):
return True
return NotImplemented
if hasattr(typing, 'AsyncContextManager'):
AsyncContextManager = typing.AsyncContextManager
__all__.append('AsyncContextManager')
elif hasattr(contextlib, 'AbstractAsyncContextManager'):
class AsyncContextManager(typing.Generic[T_co],
metaclass=_ExtensionsGenericMeta,
extra=contextlib.AbstractAsyncContextManager):
__slots__ = ()
__all__.append('AsyncContextManager')
elif sys.version_info[:2] >= (3, 5):
exec("""
class AsyncContextManager(typing.Generic[T_co]):
__slots__ = ()
async def __aenter__(self):
return self
@abc.abstractmethod
async def __aexit__(self, exc_type, exc_value, traceback):
return None
@classmethod
def __subclasshook__(cls, C):
if cls is AsyncContextManager:
return _check_methods_in_mro(C, "__aenter__", "__aexit__")
return NotImplemented
__all__.append('AsyncContextManager')
""")
if hasattr(typing, 'DefaultDict'):
DefaultDict = typing.DefaultDict
elif _geqv_defined:
class DefaultDict(collections.defaultdict, typing.MutableMapping[KT, VT],
metaclass=_ExtensionsGenericMeta,
extra=collections.defaultdict):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, DefaultDict):
return collections.defaultdict(*args, **kwds)
return _generic_new(collections.defaultdict, cls, *args, **kwds)
else:
class DefaultDict(collections.defaultdict, typing.MutableMapping[KT, VT],
metaclass=_ExtensionsGenericMeta,
extra=collections.defaultdict):
__slots__ = ()
def __new__(cls, *args, **kwds):
if cls._gorg is DefaultDict:
return collections.defaultdict(*args, **kwds)
return _generic_new(collections.defaultdict, cls, *args, **kwds)
if hasattr(typing, 'Counter'):
Counter = typing.Counter
elif (3, 5, 0) <= sys.version_info[:3] <= (3, 5, 1):
assert _geqv_defined
_TInt = typing.TypeVar('_TInt')
class _CounterMeta(typing.GenericMeta):
"""Metaclass for Counter"""
def __getitem__(self, item):
return super().__getitem__((item, int))
class Counter(collections.Counter,
typing.Dict[T, int],
metaclass=_CounterMeta,
extra=collections.Counter):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, Counter):
return collections.Counter(*args, **kwds)
return _generic_new(collections.Counter, cls, *args, **kwds)
elif _geqv_defined:
class Counter(collections.Counter,
typing.Dict[T, int],
metaclass=_ExtensionsGenericMeta, extra=collections.Counter):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, Counter):
return collections.Counter(*args, **kwds)
return _generic_new(collections.Counter, cls, *args, **kwds)
else:
class Counter(collections.Counter,
typing.Dict[T, int],
metaclass=_ExtensionsGenericMeta, extra=collections.Counter):
__slots__ = ()
def __new__(cls, *args, **kwds):
if cls._gorg is Counter:
return collections.Counter(*args, **kwds)
return _generic_new(collections.Counter, cls, *args, **kwds)
if hasattr(typing, 'ChainMap'):
ChainMap = typing.ChainMap
__all__.append('ChainMap')
elif hasattr(collections, 'ChainMap'):
# ChainMap only exists in 3.3+
if _geqv_defined:
class ChainMap(collections.ChainMap, typing.MutableMapping[KT, VT],
metaclass=_ExtensionsGenericMeta,
extra=collections.ChainMap):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, ChainMap):
return collections.ChainMap(*args, **kwds)
return _generic_new(collections.ChainMap, cls, *args, **kwds)
else:
class ChainMap(collections.ChainMap, typing.MutableMapping[KT, VT],
metaclass=_ExtensionsGenericMeta,
extra=collections.ChainMap):
__slots__ = ()
def __new__(cls, *args, **kwds):
if cls._gorg is ChainMap:
return collections.ChainMap(*args, **kwds)
return _generic_new(collections.ChainMap, cls, *args, **kwds)
__all__.append('ChainMap')
if _define_guard('AsyncGenerator'):
class AsyncGenerator(AsyncIterator[T_co], typing.Generic[T_co, T_contra],
metaclass=_ExtensionsGenericMeta,
extra=collections_abc.AsyncGenerator):
__slots__ = ()
if hasattr(typing, 'NewType'):
NewType = typing.NewType
else:
def NewType(name, tp):
"""NewType creates simple unique types with almost zero
runtime overhead. NewType(name, tp) is considered a subtype of tp
by static type checkers. At runtime, NewType(name, tp) returns
a dummy function that simply returns its argument. Usage::
UserId = NewType('UserId', int)
def name_by_id(user_id: UserId) -> str:
...
UserId('user') # Fails type check
name_by_id(42) # Fails type check
name_by_id(UserId(42)) # OK
num = UserId(5) + 1 # type: int
"""
def new_type(x):
return x
new_type.__name__ = name
new_type.__supertype__ = tp
return new_type
if hasattr(typing, 'Text'):
Text = typing.Text
else:
Text = str
if hasattr(typing, 'TYPE_CHECKING'):
TYPE_CHECKING = typing.TYPE_CHECKING
else:
# Constant that's True when type checking, but False here.
TYPE_CHECKING = False
def _gorg(cls):
"""This function exists for compatibility with old typing versions."""
assert isinstance(cls, GenericMeta)
if hasattr(cls, '_gorg'):
return cls._gorg
while cls.__origin__ is not None:
cls = cls.__origin__
return cls
if OLD_GENERICS:
def _next_in_mro(cls): # noqa
"""This function exists for compatibility with old typing versions."""
next_in_mro = object
for i, c in enumerate(cls.__mro__[:-1]):
if isinstance(c, GenericMeta) and _gorg(c) is Generic:
next_in_mro = cls.__mro__[i + 1]
return next_in_mro
_PROTO_WHITELIST = ['Callable', 'Awaitable',
'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator',
'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',
'ContextManager', 'AsyncContextManager']
def _get_protocol_attrs(cls):
attrs = set()
for base in cls.__mro__[:-1]: # without object
if base.__name__ in ('Protocol', 'Generic'):
continue
annotations = getattr(base, '__annotations__', {})
for attr in list(base.__dict__.keys()) + list(annotations.keys()):
if (not attr.startswith('_abc_') and attr not in (
'__abstractmethods__', '__annotations__', '__weakref__',
'_is_protocol', '_is_runtime_protocol', '__dict__',
'__args__', '__slots__',
'__next_in_mro__', '__parameters__', '__origin__',
'__orig_bases__', '__extra__', '__tree_hash__',
'__doc__', '__subclasshook__', '__init__', '__new__',
'__module__', '_MutableMapping__marker', '_gorg')):
attrs.add(attr)
return attrs
def _is_callable_members_only(cls):
return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls))
if hasattr(typing, 'Protocol'):
Protocol = typing.Protocol
elif HAVE_PROTOCOLS and not PEP_560:
class _ProtocolMeta(GenericMeta):
"""Internal metaclass for Protocol.
This exists so Protocol classes can be generic without deriving
from Generic.
"""
if not OLD_GENERICS:
def __new__(cls, name, bases, namespace,
tvars=None, args=None, origin=None, extra=None, orig_bases=None):
# This is just a version copied from GenericMeta.__new__ that
# includes "Protocol" special treatment. (Comments removed for brevity.)
assert extra is None # Protocols should not have extra
if tvars is not None:
assert origin is not None
assert all(isinstance(t, TypeVar) for t in tvars), tvars
else:
tvars = _type_vars(bases)
gvars = None
for base in bases:
if base is Generic:
raise TypeError("Cannot inherit from plain Generic")
if (isinstance(base, GenericMeta) and
base.__origin__ in (Generic, Protocol)):
if gvars is not None:
raise TypeError(
"Cannot inherit from Generic[...] or"
" Protocol[...] multiple times.")
gvars = base.__parameters__
if gvars is None:
gvars = tvars
else:
tvarset = set(tvars)
gvarset = set(gvars)
if not tvarset <= gvarset:
raise TypeError(
"Some type variables (%s) "
"are not listed in %s[%s]" %
(", ".join(str(t) for t in tvars if t not in gvarset),
"Generic" if any(b.__origin__ is Generic
for b in bases) else "Protocol",
", ".join(str(g) for g in gvars)))
tvars = gvars
initial_bases = bases
if (extra is not None and type(extra) is abc.ABCMeta and
extra not in bases):
bases = (extra,) + bases
bases = tuple(_gorg(b) if isinstance(b, GenericMeta) else b
for b in bases)
if any(isinstance(b, GenericMeta) and b is not Generic for b in bases):
bases = tuple(b for b in bases if b is not Generic)
namespace.update({'__origin__': origin, '__extra__': extra})
self = super(GenericMeta, cls).__new__(cls, name, bases, namespace,
_root=True)
super(GenericMeta, self).__setattr__('_gorg',
self if not origin else
_gorg(origin))
self.__parameters__ = tvars
self.__args__ = tuple(... if a is _TypingEllipsis else
() if a is _TypingEmpty else
a for a in args) if args else None
self.__next_in_mro__ = _next_in_mro(self)
if orig_bases is None:
self.__orig_bases__ = initial_bases
elif origin is not None:
self._abc_registry = origin._abc_registry
self._abc_cache = origin._abc_cache
if hasattr(self, '_subs_tree'):
self.__tree_hash__ = (hash(self._subs_tree()) if origin else
super(GenericMeta, self).__hash__())
return self
def __init__(cls, *args, **kwargs):
super().__init__(*args, **kwargs)
if not cls.__dict__.get('_is_protocol', None):
cls._is_protocol = any(b is Protocol or
isinstance(b, _ProtocolMeta) and
b.__origin__ is Protocol
for b in cls.__bases__)
if cls._is_protocol:
for base in cls.__mro__[1:]:
if not (base in (object, Generic) or
base.__module__ == 'collections.abc' and
base.__name__ in _PROTO_WHITELIST or
isinstance(base, TypingMeta) and base._is_protocol or
isinstance(base, GenericMeta) and
base.__origin__ is Generic):
raise TypeError('Protocols can only inherit from other'
' protocols, got %r' % base)
def _no_init(self, *args, **kwargs):
if type(self)._is_protocol:
raise TypeError('Protocols cannot be instantiated')
cls.__init__ = _no_init
def _proto_hook(other):
if not cls.__dict__.get('_is_protocol', None):
return NotImplemented
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
def __instancecheck__(self, instance):
# We need this method for situations where attributes are
# assigned in __init__.
if ((not getattr(self, '_is_protocol', False) or
_is_callable_members_only(self)) and
issubclass(instance.__class__, self)):
return True
if self._is_protocol:
if all(hasattr(instance, attr) and
(not callable(getattr(self, attr, None)) or
getattr(instance, attr) is not None)
for attr in _get_protocol_attrs(self)):
return True
return super(GenericMeta, self).__instancecheck__(instance)
def __subclasscheck__(self, cls):
if self.__origin__ is not None:
if sys._getframe(1).f_globals['__name__'] not in ['abc', 'functools']:
raise TypeError("Parameterized generics cannot be used with class "
"or instance checks")
return False
if (self.__dict__.get('_is_protocol', None) and
not self.__dict__.get('_is_runtime_protocol', None)):
if sys._getframe(1).f_globals['__name__'] in ['abc',
'functools',
'typing']:
return False
raise TypeError("Instance and class checks can only be used with"
" @runtime protocols")
if (self.__dict__.get('_is_runtime_protocol', None) and
not _is_callable_members_only(self)):
if sys._getframe(1).f_globals['__name__'] in ['abc',
'functools',
'typing']:
return super(GenericMeta, self).__subclasscheck__(cls)
raise TypeError("Protocols with non-method members"
" don't support issubclass()")
return super(GenericMeta, self).__subclasscheck__(cls)
if not OLD_GENERICS:
@_tp_cache
def __getitem__(self, params):
# We also need to copy this from GenericMeta.__getitem__ to get
# special treatment of "Protocol". (Comments removed for brevity.)
if not isinstance(params, tuple):
params = (params,)
if not params and _gorg(self) is not Tuple:
raise TypeError(
"Parameter list to %s[...] cannot be empty" % self.__qualname__)
msg = "Parameters to generic types must be types."
params = tuple(_type_check(p, msg) for p in params)
if self in (Generic, Protocol):
if not all(isinstance(p, TypeVar) for p in params):
raise TypeError(
"Parameters to %r[...] must all be type variables" % self)
if len(set(params)) != len(params):
raise TypeError(
"Parameters to %r[...] must all be unique" % self)
tvars = params
args = params
elif self in (Tuple, Callable):
tvars = _type_vars(params)
args = params
elif self.__origin__ in (Generic, Protocol):
raise TypeError("Cannot subscript already-subscripted %s" %
repr(self))
else:
_check_generic(self, params)
tvars = _type_vars(params)
args = params
prepend = (self,) if self.__origin__ is None else ()
return self.__class__(self.__name__,
prepend + self.__bases__,
_no_slots_copy(self.__dict__),
tvars=tvars,
args=args,
origin=self,
extra=self.__extra__,
orig_bases=self.__orig_bases__)
class Protocol(metaclass=_ProtocolMeta):
"""Base class for protocol classes. Protocol classes are defined as::
class Proto(Protocol):
def meth(self) -> int:
...
Such classes are primarily used with static type checkers that recognize
structural subtyping (static duck-typing), for example::
class C:
def meth(self) -> int:
return 0
def func(x: Proto) -> int:
return x.meth()
func(C()) # Passes static type check
See PEP 544 for details. Protocol classes decorated with
@typing_extensions.runtime act as simple-minded runtime protocol that checks
only the presence of given attributes, ignoring their type signatures.
Protocol classes can be generic, they are defined as::
class GenProto({bases}):
def meth(self) -> T:
...
"""
__slots__ = ()
_is_protocol = True
def __new__(cls, *args, **kwds):
if _gorg(cls) is Protocol:
raise TypeError("Type Protocol cannot be instantiated; "
"it can be used only as a base class")
if OLD_GENERICS:
return _generic_new(_next_in_mro(cls), cls, *args, **kwds)
return _generic_new(cls.__next_in_mro__, cls, *args, **kwds)
if Protocol.__doc__ is not None:
Protocol.__doc__ = Protocol.__doc__.format(bases="Protocol, Generic[T]" if
OLD_GENERICS else "Protocol[T]")
elif PEP_560:
from typing import _type_check, _GenericAlias, _collect_type_vars # noqa
class _ProtocolMeta(abc.ABCMeta):
# This metaclass is a bit unfortunate and exists only because of the lack
# of __instancehook__.
def __instancecheck__(cls, instance):
# We need this method for situations where attributes are
# assigned in __init__.
if ((not getattr(cls, '_is_protocol', False) or
_is_callable_members_only(cls)) and
issubclass(instance.__class__, cls)):
return True
if cls._is_protocol:
if all(hasattr(instance, attr) and
(not callable(getattr(cls, attr, None)) or
getattr(instance, attr) is not None)
for attr in _get_protocol_attrs(cls)):
return True
return super().__instancecheck__(instance)
class Protocol(metaclass=_ProtocolMeta):
# There is quite a lot of overlapping code with typing.Generic.
# Unfortunately it is hard to avoid this while these live in two different
# modules. The duplicated code will be removed when Protocol is moved to typing.
"""Base class for protocol classes. Protocol classes are defined as::
class Proto(Protocol):
def meth(self) -> int:
...
Such classes are primarily used with static type checkers that recognize
structural subtyping (static duck-typing), for example::
class C:
def meth(self) -> int:
return 0
def func(x: Proto) -> int:
return x.meth()
func(C()) # Passes static type check
See PEP 544 for details. Protocol classes decorated with
@typing_extensions.runtime act as simple-minded runtime protocol that checks
only the presence of given attributes, ignoring their type signatures.
Protocol classes can be generic, they are defined as::
class GenProto(Protocol[T]):
def meth(self) -> T:
...
"""
__slots__ = ()
_is_protocol = True
def __new__(cls, *args, **kwds):
if cls is Protocol:
raise TypeError("Type Protocol cannot be instantiated; "
"it can only be used as a base class")
return super().__new__(cls)
@_tp_cache
def __class_getitem__(cls, params):
if not isinstance(params, tuple):
params = (params,)
if not params and cls is not Tuple:
raise TypeError(
"Parameter list to {}[...] cannot be empty".format(cls.__qualname__))
msg = "Parameters to generic types must be types."
params = tuple(_type_check(p, msg) for p in params)
if cls is Protocol:
# Generic can only be subscripted with unique type variables.
if not all(isinstance(p, TypeVar) for p in params):
i = 0
while isinstance(params[i], TypeVar):
i += 1
raise TypeError(
"Parameters to Protocol[...] must all be type variables."
" Parameter {} is {}".format(i + 1, 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)
return _GenericAlias(cls, params)
def __init_subclass__(cls, *args, **kwargs):
tvars = []
if '__orig_bases__' in cls.__dict__:
error = Generic in cls.__orig_bases__
else:
error = Generic in cls.__bases__
if error:
raise TypeError("Cannot inherit from plain Generic")
if '__orig_bases__' in cls.__dict__:
tvars = _collect_type_vars(cls.__orig_bases__)
# Look for Generic[T1, ..., Tn] or Protocol[T1, ..., Tn].
# If found, tvars must be a subset of it.
# If not found, tvars is it.
# Also check for and reject plain Generic,
# and reject multiple Generic[...] and/or Protocol[...].
gvars = None
for base in cls.__orig_bases__:
if (isinstance(base, _GenericAlias) and
base.__origin__ in (Generic, Protocol)):
# for error messages
the_base = 'Generic' if base.__origin__ is Generic else 'Protocol'
if gvars is not None:
raise TypeError(
"Cannot inherit from Generic[...]"
" and/or Protocol[...] multiple types.")
gvars = base.__parameters__
if gvars is None:
gvars = tvars
else:
tvarset = set(tvars)
gvarset = set(gvars)
if not tvarset <= gvarset:
s_vars = ', '.join(str(t) for t in tvars if t not in gvarset)
s_args = ', '.join(str(g) for g in gvars)
raise TypeError("Some type variables ({}) are"
" not listed in {}[{}]".format(s_vars,
the_base, s_args))
tvars = gvars
cls.__parameters__ = tuple(tvars)
# 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, 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'
' protocols, got %r' % base)
def _no_init(self, *args, **kwargs):
if type(self)._is_protocol:
raise TypeError('Protocols cannot be instantiated')
cls.__init__ = _no_init
if hasattr(typing, 'runtime_checkable'):
runtime_checkable = typing.runtime_checkable
elif HAVE_PROTOCOLS:
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,'
' got %r' % cls)
cls._is_runtime_protocol = True
return cls
if HAVE_PROTOCOLS:
# Exists for backwards compatibility.
runtime = runtime_checkable
if sys.version_info[:2] >= (3, 9):
# 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
TypedDict = typing.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__ = '($cls, _typename, _fields=None, /, **kwargs)'
def _typeddict_new(*args, total=True, **kwargs):
if not args:
raise TypeError('TypedDict.__new__(): not enough arguments')
_, args = args[0], args[1:] # allow the "cls" keyword be passed
if args:
typename, args = args[0], args[1:] # allow the "_typename" keyword be passed
elif '_typename' in kwargs:
typename = kwargs.pop('_typename')
import warnings
warnings.warn("Passing '_typename' as keyword argument is deprecated",
DeprecationWarning, stacklevel=2)
else:
raise TypeError("TypedDict.__new__() missing 1 required positional "
"argument: '_typename'")
if args:
try:
fields, = args # allow the "_fields" keyword be passed
except ValueError:
raise TypeError('TypedDict.__new__() takes from 2 to 3 '
'positional arguments but {} '
'were given'.format(len(args) + 2))
elif '_fields' in kwargs and len(kwargs) == 1:
fields = kwargs.pop('_fields')
import warnings
warnings.warn("Passing '_fields' as keyword argument is deprecated",
DeprecationWarning, stacklevel=2)
else:
fields = None
if fields is None:
fields = kwargs
elif kwargs:
raise TypeError("TypedDict takes either a dict or keyword arguments,"
" but not both")
ns = {'__annotations__': dict(fields), '__total__': total}
try:
# Setting correct module is necessary to make typed dict classes pickleable.
ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
return _TypedDictMeta(typename, (), ns)
_typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,'
' /, *, total=True, **kwargs)')
class _TypedDictMeta(type):
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
tp_dict = super(_TypedDictMeta, cls).__new__(cls, name, (dict,), ns)
annotations = {}
own_annotations = ns.get('__annotations__', {})
own_annotation_keys = set(own_annotations.keys())
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)
if total:
required_keys.update(own_annotation_keys)
else:
optional_keys.update(own_annotation_keys)
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+
"""
# Python 3.9+ has PEP 593 (Annotated and modified get_type_hints)
if hasattr(typing, 'Annotated'):
Annotated = typing.Annotated
get_type_hints = typing.get_type_hints
# Not exported and not a public API, but needed for get_origin() and get_args()
# to work.
_AnnotatedAlias = typing._AnnotatedAlias
elif PEP_560:
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 "typing_extensions.Annotated[{}, {}]".format(
typing._type_repr(self.__origin__),
", ".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.")
@_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).")
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(
"Cannot subclass {}.Annotated".format(cls.__module__)
)
def _strip_annotations(t):
"""Strips the annotations from a given type.
"""
if isinstance(t, _AnnotatedAlias):
return _strip_annotations(t.__origin__)
if isinstance(t, typing._GenericAlias):
stripped_args = tuple(_strip_annotations(a) for a in t.__args__)
if stripped_args == t.__args__:
return t
res = t.copy_with(stripped_args)
res._special = t._special
return res
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, ...]' 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.
"""
hint = typing.get_type_hints(obj, globalns=globalns, localns=localns)
if include_extras:
return hint
return {k: _strip_annotations(t) for k, t in hint.items()}
elif HAVE_ANNOTATED:
def _is_dunder(name):
"""Returns True if name is a __dunder_variable_name__."""
return len(name) > 4 and name.startswith('__') and name.endswith('__')
# Prior to Python 3.7 types did not have `copy_with`. A lot of the equality
# checks, argument expansion etc. are done on the _subs_tre. As a result we
# can't provide a get_type_hints function that strips out annotations.
class AnnotatedMeta(typing.GenericMeta):
"""Metaclass for Annotated"""
def __new__(cls, name, bases, namespace, **kwargs):
if any(b is not object for b in bases):
raise TypeError("Cannot subclass " + str(Annotated))
return super().__new__(cls, name, bases, namespace, **kwargs)
@property
def __metadata__(self):
return self._subs_tree()[2]
def _tree_repr(self, tree):
cls, origin, metadata = tree
if not isinstance(origin, tuple):
tp_repr = typing._type_repr(origin)
else:
tp_repr = origin[0]._tree_repr(origin)
metadata_reprs = ", ".join(repr(arg) for arg in metadata)
return '%s[%s, %s]' % (cls, tp_repr, metadata_reprs)
def _subs_tree(self, tvars=None, args=None): # noqa
if self is Annotated:
return Annotated
res = super()._subs_tree(tvars=tvars, args=args)
# Flatten nested Annotated
if isinstance(res[1], tuple) and res[1][0] is Annotated:
sub_tp = res[1][1]
sub_annot = res[1][2]
return (Annotated, sub_tp, sub_annot + res[2])
return res
def _get_cons(self):
"""Return the class used to create instance of this type."""
if self.__origin__ is None:
raise TypeError("Cannot get the underlying type of a "
"non-specialized Annotated type.")
tree = self._subs_tree()
while isinstance(tree, tuple) and tree[0] is Annotated:
tree = tree[1]
if isinstance(tree, tuple):
return tree[0]
else:
return tree
@_tp_cache
def __getitem__(self, params):
if not isinstance(params, tuple):
params = (params,)
if self.__origin__ is not None: # specializing an instantiated type
return super().__getitem__(params)
elif not isinstance(params, tuple) or len(params) < 2:
raise TypeError("Annotated[...] should be instantiated "
"with at least two arguments (a type and an "
"annotation).")
else:
msg = "Annotated[t, ...]: t must be a type."
tp = typing._type_check(params[0], msg)
metadata = tuple(params[1:])
return self.__class__(
self.__name__,
self.__bases__,
_no_slots_copy(self.__dict__),
tvars=_type_vars((tp,)),
# Metadata is a tuple so it won't be touched by _replace_args et al.
args=(tp, metadata),
origin=self,
)
def __call__(self, *args, **kwargs):
cons = self._get_cons()
result = cons(*args, **kwargs)
try:
result.__orig_class__ = self
except AttributeError:
pass
return result
def __getattr__(self, attr):
# For simplicity we just don't relay all dunder names
if self.__origin__ is not None and not _is_dunder(attr):
return getattr(self._get_cons(), attr)
raise AttributeError(attr)
def __setattr__(self, attr, value):
if _is_dunder(attr) or attr.startswith('_abc_'):
super().__setattr__(attr, value)
elif self.__origin__ is None:
raise AttributeError(attr)
else:
setattr(self._get_cons(), attr, value)
def __instancecheck__(self, obj):
raise TypeError("Annotated cannot be used with isinstance().")
def __subclasscheck__(self, cls):
raise TypeError("Annotated cannot be used with issubclass().")
class Annotated(metaclass=AnnotatedMeta):
"""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, the remaining
arguments are kept as a tuple in the __metadata__ 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()]
"""
# Python 3.8 has get_origin() and get_args() but those implementations aren't
# Annotated-aware, so we can't use those, only Python 3.9 versions will do.
if sys.version_info[:2] >= (3, 9):
get_origin = typing.get_origin
get_args = typing.get_args
elif PEP_560:
from typing import _GenericAlias # noqa
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
"""
if isinstance(tp, _AnnotatedAlias):
return Annotated
if isinstance(tp, _GenericAlias):
return tp.__origin__
if tp is Generic:
return 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, _GenericAlias):
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 ()