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 from typing import _GenericAlias 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', 'Concatenate', 'Final', 'ParamSpec', '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', 'OrderedDict', 'TypedDict', # Structural checks, a.k.a. protocols. 'SupportsIndex', # One-off things. 'final', 'IntVar', 'Literal', 'NewType', 'overload', 'Text', 'TypeAlias', 'TypeGuard', '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, 'OrderedDict'): OrderedDict = typing.OrderedDict elif (3, 7, 0) <= sys.version_info[:3] < (3, 7, 2): OrderedDict = typing._alias(collections.OrderedDict, (KT, VT)) elif _geqv_defined: class OrderedDict(collections.OrderedDict, typing.MutableMapping[KT, VT], metaclass=_ExtensionsGenericMeta, extra=collections.OrderedDict): __slots__ = () def __new__(cls, *args, **kwds): if _geqv(cls, OrderedDict): return collections.OrderedDict(*args, **kwds) return _generic_new(collections.OrderedDict, cls, *args, **kwds) else: class OrderedDict(collections.OrderedDict, typing.MutableMapping[KT, VT], metaclass=_ExtensionsGenericMeta, extra=collections.OrderedDict): __slots__ = () def __new__(cls, *args, **kwds): if cls._gorg is OrderedDict: return collections.OrderedDict(*args, **kwds) return _generic_new(collections.OrderedDict, 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: def _no_init(self, *args, **kwargs): if type(self)._is_protocol: raise TypeError('Protocols cannot be instantiated') 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) 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, _collect_type_vars # noqa def _no_init(self, *args, **kwargs): if type(self)._is_protocol: raise TypeError('Protocols cannot be instantiated') 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) 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 hasattr(typing, 'SupportsIndex'): SupportsIndex = typing.SupportsIndex elif HAVE_PROTOCOLS: @runtime_checkable class SupportsIndex(Protocol): __slots__ = () @abc.abstractmethod def __index__(self) -> int: pass if sys.version_info >= (3, 9, 2): # 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 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__ = '($cls, _typename, _fields=None, /, **kwargs)' def _typeddict_new(*args, total=True, **kwargs): if not args: raise TypeError('TypedDict.__new__(): not enough arguments') _, args = args[0], args[1:] # allow the "cls" keyword be passed if args: typename, args = args[0], args[1:] # allow the "_typename" keyword be passed elif '_typename' in kwargs: typename = kwargs.pop('_typename') import warnings warnings.warn("Passing '_typename' as keyword argument is deprecated", DeprecationWarning, stacklevel=2) else: raise TypeError("TypedDict.__new__() missing 1 required positional " "argument: '_typename'") if args: try: fields, = args # allow the "_fields" keyword be passed except ValueError: raise TypeError('TypedDict.__new__() takes from 2 to 3 ' 'positional arguments but {} ' 'were given'.format(len(args) + 2)) elif '_fields' in kwargs and len(kwargs) == 1: fields = kwargs.pop('_fields') import warnings warnings.warn("Passing '_fields' as keyword argument is deprecated", DeprecationWarning, stacklevel=2) else: fields = None if fields is None: fields = kwargs elif kwargs: raise TypeError("TypedDict takes either a dict or keyword arguments," " but not both") ns = {'__annotations__': dict(fields)} try: # Setting correct module is necessary to make typed dict classes pickleable. ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__') except (AttributeError, ValueError): pass return _TypedDictMeta(typename, (), ns, total=total) _typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,' ' /, *, total=True, **kwargs)') class _TypedDictMeta(type): def __init__(cls, name, bases, ns, total=True): # In Python 3.4 and 3.5 the __init__ method also needs to support the # keyword arguments. # See https://www.python.org/dev/peps/pep-0487/#implementation-details super(_TypedDictMeta, cls).__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 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. # Similarly, Python 3.9's implementation doesn't support ParamSpecArgs and # ParamSpecKwargs. if sys.version_info[:2] >= (3, 10): get_origin = typing.get_origin get_args = typing.get_args elif PEP_560: try: # 3.9+ from typing import _BaseGenericAlias except ImportError: _BaseGenericAlias = _GenericAlias try: # 3.9+ from typing import GenericAlias except ImportError: GenericAlias = _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, (_GenericAlias, GenericAlias, _BaseGenericAlias, ParamSpecArgs, ParamSpecKwargs)): 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, 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 () if hasattr(typing, 'TypeAlias'): TypeAlias = typing.TypeAlias 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("{} is not subscriptable".format(self)) elif sys.version_info[:2] >= (3, 7): 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.""") elif hasattr(typing, '_FinalTypingBase'): class _TypeAliasMeta(typing.TypingMeta): """Metaclass for TypeAlias""" def __repr__(self): return 'typing_extensions.TypeAlias' class _TypeAliasBase(typing._FinalTypingBase, metaclass=_TypeAliasMeta, _root=True): """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. """ __slots__ = () def __instancecheck__(self, obj): raise TypeError("TypeAlias cannot be used with isinstance().") def __subclasscheck__(self, cls): raise TypeError("TypeAlias cannot be used with issubclass().") def __repr__(self): return 'typing_extensions.TypeAlias' TypeAlias = _TypeAliasBase(_root=True) else: class _TypeAliasMeta(typing.TypingMeta): """Metaclass for TypeAlias""" def __instancecheck__(self, obj): raise TypeError("TypeAlias cannot be used with isinstance().") def __subclasscheck__(self, cls): raise TypeError("TypeAlias cannot be used with issubclass().") def __call__(self, *args, **kwargs): raise TypeError("Cannot instantiate TypeAlias") class TypeAlias(metaclass=_TypeAliasMeta, _root=True): """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. """ __slots__ = () # Python 3.10+ has PEP 612 if hasattr(typing, 'ParamSpecArgs'): ParamSpecArgs = typing.ParamSpecArgs ParamSpecKwargs = typing.ParamSpecKwargs 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 "{}.args".format(self.__origin__.__name__) 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 "{}.kwargs".format(self.__origin__.__name__) if hasattr(typing, 'ParamSpec'): ParamSpec = typing.ParamSpec else: # Inherits from list as a workaround for Callable checks in Python < 3.9.2. class ParamSpec(list): """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__ = 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): 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 # 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 if not PEP_560: # Only needed in 3.6 and lower. def _get_type_vars(self, tvars): if self not in tvars: tvars.append(self) # 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__. if PEP_560: __class__ = typing._GenericAlias elif sys.version_info[:3] == (3, 5, 2): __class__ = typing.TypingMeta else: __class__ = typing._TypingBase # Flag in 3.8. _special = False # Attribute in 3.6 and earlier. if sys.version_info[:3] == (3, 5, 2): _gorg = typing.GenericMeta else: _gorg = typing.Generic def __init__(self, origin, args): super().__init__(args) self.__origin__ = origin self.__args__ = args def __repr__(self): _type_repr = typing._type_repr return '{origin}[{args}]' \ .format(origin=_type_repr(self.__origin__), args=', '.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, (TypeVar, ParamSpec))) if not PEP_560: # Only required in 3.6 and lower. def _get_type_vars(self, tvars): if self.__origin__ and self.__parameters__: typing._get_type_vars(self.__parameters__, tvars) @_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) if hasattr(typing, 'Concatenate'): Concatenate = typing.Concatenate _ConcatenateGenericAlias = typing._ConcatenateGenericAlias # noqa 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) elif sys.version_info[:2] >= (3, 7): 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. """) elif hasattr(typing, '_FinalTypingBase'): class _ConcatenateAliasMeta(typing.TypingMeta): """Metaclass for Concatenate.""" def __repr__(self): return 'typing_extensions.Concatenate' class _ConcatenateAliasBase(typing._FinalTypingBase, metaclass=_ConcatenateAliasMeta, _root=True): """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. """ __slots__ = () def __instancecheck__(self, obj): raise TypeError("Concatenate cannot be used with isinstance().") def __subclasscheck__(self, cls): raise TypeError("Concatenate cannot be used with issubclass().") def __repr__(self): return 'typing_extensions.Concatenate' def __getitem__(self, parameters): return _concatenate_getitem(self, parameters) Concatenate = _ConcatenateAliasBase(_root=True) # For 3.5.0 - 3.5.2 else: class _ConcatenateAliasMeta(typing.TypingMeta): """Metaclass for Concatenate.""" def __instancecheck__(self, obj): raise TypeError("TypeAlias cannot be used with isinstance().") def __subclasscheck__(self, cls): raise TypeError("TypeAlias cannot be used with issubclass().") def __call__(self, *args, **kwargs): raise TypeError("Cannot instantiate TypeAlias") def __getitem__(self, parameters): return _concatenate_getitem(self, parameters) class Concatenate(metaclass=_ConcatenateAliasMeta, _root=True): """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. """ __slots__ = () if hasattr(typing, 'TypeGuard'): TypeGuard = typing.TypeGuard 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, '{} accepts only single type.'.format(self)) return _GenericAlias(self, (item,)) elif sys.version_info[:2] >= (3, 7): class _TypeGuardForm(typing._SpecialForm, _root=True): def __repr__(self): return 'typing_extensions.' + self._name def __getitem__(self, parameters): item = typing._type_check(parameters, '{} accepts only a single type'.format(self._name)) return _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). """) elif hasattr(typing, '_FinalTypingBase'): class _TypeGuard(typing._FinalTypingBase, _root=True): """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). """ __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 a 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, _TypeGuard): return NotImplemented if self.__type__ is not None: return self.__type__ == other.__type__ return self is other TypeGuard = _TypeGuard(_root=True) else: class _TypeGuardMeta(typing.TypingMeta): """Metaclass for TypeGuard""" 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("TypeGuard cannot be used with isinstance().") def __subclasscheck__(self, cls): raise TypeError("TypeGuard 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 hasattr(other, "__type__"): return NotImplemented if self.__type__ is not None: return self.__type__ == other.__type__ return self is other class TypeGuard(typing.Final, metaclass=_TypeGuardMeta, _root=True): """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). """ __type__ = None