Source code for typing

The typing module: Support for gradual typing as defined by PEP 484.

At large scale, the structure of the module is following:
* Imports and exports, all public names should be explicitly added to __all__.
* Internal helper functions: these should never be used in code outside this module.
* _SpecialForm and its instances (special forms): Any, NoReturn, ClassVar, Union, Optional
* Two classes whose instances can be type arguments in addition to types: ForwardRef and TypeVar
* The core of internal generics API: _GenericAlias and _VariadicGenericAlias, the latter is
  currently only used by Tuple and Callable. All subscripted types like X[int], Union[int, str],
  etc., are instances of either of these classes.
* The public counterpart of the generics API consists of two classes: Generic and Protocol.
* Public helper functions: get_type_hints, overload, cast, no_type_check,
* Generic aliases for ABCs and few additional protocols.
* Special types: NewType, NamedTuple, TypedDict.
* Wrapper submodules for re and io related types.

from abc import abstractmethod, ABCMeta
import collections
import contextlib
import functools
import operator
import re as stdlib_re  # Avoid confusion with the re we export.
import sys
import types
from types import WrapperDescriptorType, MethodWrapperType, MethodDescriptorType

# Please keep __all__ alphabetized within each category.
__all__ = [
    # Super-special typing primitives.

    # ABCs (from
    'AbstractSet',  #

    # Structural checks, a.k.a. protocols.

    # Concrete collection types.
    'NamedTuple',  # Not really a type.
    'TypedDict',  # Not really a type.

    # One-off things.

# The pseudo-submodules 're' and 'io' are part of the public
# namespace, but excluded from __all__ because they might stomp on
# legitimate imports of those modules.

def _type_check(arg, msg, is_argument=True):
    """Check that the argument is a type, and return it (internal helper).

    As a special case, accept None and return type(None) instead. Also wrap strings
    into ForwardRef instances. Consider several corner cases, for example plain
    special forms like Union are not valid, while Union[int, str] is OK, etc.
    The msg argument is a human-readable error message, e.g::

        "Union[arg, ...]: arg should be a type."

    We append the repr() of the actual value (truncated to 100 chars).
    invalid_generic_forms = (Generic, Protocol)
    if is_argument:
        invalid_generic_forms = invalid_generic_forms + (ClassVar, Final)

    if arg is None:
        return type(None)
    if isinstance(arg, str):
        return ForwardRef(arg)
    if (isinstance(arg, _GenericAlias) and
            arg.__origin__ in invalid_generic_forms):
        raise TypeError(f"{arg} is not valid as type argument")
    if (isinstance(arg, _SpecialForm) and arg not in (Any, NoReturn) or
            arg in (Generic, Protocol)):
        raise TypeError(f"Plain {arg} is not valid as type argument")
    if isinstance(arg, (type, TypeVar, ForwardRef)):
        return arg
    if not callable(arg):
        raise TypeError(f"{msg} Got {arg!r:.100}.")
    return arg

def _type_repr(obj):
    """Return the repr() of an object, special-casing types (internal helper).

    If obj is a type, we return a shorter version than the default
    type.__repr__, based on the module and qualified name, which is
    typically enough to uniquely identify a type.  For everything
    else, we fall back on repr(obj).
    if isinstance(obj, type):
        if obj.__module__ == 'builtins':
            return obj.__qualname__
        return f'{obj.__module__}.{obj.__qualname__}'
    if obj is ...:
    if isinstance(obj, types.FunctionType):
        return obj.__name__
    return repr(obj)

def _collect_type_vars(types):
    """Collect all type variable contained in types in order of
    first appearance (lexicographic order). For example::

        _collect_type_vars((T, List[S, T])) == (T, S)
    tvars = []
    for t in types:
        if isinstance(t, TypeVar) and t not in tvars:
        if isinstance(t, _GenericAlias) and not t._special:
            tvars.extend([t for t in t.__parameters__ if t not in tvars])
    return tuple(tvars)

def _subs_tvars(tp, tvars, subs):
    """Substitute type variables 'tvars' with substitutions 'subs'.
    These two must have the same length.
    if not isinstance(tp, _GenericAlias):
        return tp
    new_args = list(tp.__args__)
    for a, arg in enumerate(tp.__args__):
        if isinstance(arg, TypeVar):
            for i, tvar in enumerate(tvars):
                if arg == tvar:
                    new_args[a] = subs[i]
            new_args[a] = _subs_tvars(arg, tvars, subs)
    if tp.__origin__ is Union:
        return Union[tuple(new_args)]
    return tp.copy_with(tuple(new_args))

def _check_generic(cls, parameters):
    """Check correct count for parameters of a generic cls (internal helper).
    This gives a nice error message in case of count mismatch.
    if not cls.__parameters__:
        raise TypeError(f"{cls} is not a generic class")
    alen = len(parameters)
    elen = len(cls.__parameters__)
    if alen != elen:
        raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};"
                        f" actual {alen}, expected {elen}")

def _remove_dups_flatten(parameters):
    """An internal helper for Union creation and substitution: flatten Unions
    among parameters, then remove duplicates.
    # Flatten out Union[Union[...], ...].
    params = []
    for p in parameters:
        if isinstance(p, _GenericAlias) and p.__origin__ is Union:
        elif isinstance(p, tuple) and len(p) > 0 and p[0] is Union:
    # Weed out strict duplicates, preserving the first of each occurrence.
    all_params = set(params)
    if len(all_params) < len(params):
        new_params = []
        for t in params:
            if t in all_params:
        params = new_params
        assert not all_params, all_params
    return tuple(params)

_cleanups = []

def _tp_cache(func):
    """Internal wrapper caching __getitem__ of generic types with a fallback to
    original function for non-hashable arguments.
    cached = functools.lru_cache()(func)

    def inner(*args, **kwds):
            return cached(*args, **kwds)
        except TypeError:
            pass  # All real errors (not unhashable args) are raised below.
        return func(*args, **kwds)
    return inner

def _eval_type(t, globalns, localns):
    """Evaluate all forward reverences in the given type t.
    For use of globalns and localns see the docstring for get_type_hints().
    if isinstance(t, ForwardRef):
        return t._evaluate(globalns, localns)
    if isinstance(t, _GenericAlias):
        ev_args = tuple(_eval_type(a, globalns, localns) for a in t.__args__)
        if ev_args == t.__args__:
            return t
        res = t.copy_with(ev_args)
        res._special = t._special
        return res
    return t

class _Final:
    """Mixin to prohibit subclassing"""

    __slots__ = ('__weakref__',)

    def __init_subclass__(self, /, *args, **kwds):
        if '_root' not in kwds:
            raise TypeError("Cannot subclass special typing classes")

class _Immutable:
    """Mixin to indicate that object should not be copied."""

    def __copy__(self):
        return self

    def __deepcopy__(self, memo):
        return self

class _SpecialForm(_Final, _Immutable, _root=True):
    """Internal indicator of special typing constructs.
    See _doc instance attribute for specific docs.

    __slots__ = ('_name', '_doc')

    def __new__(cls, *args, **kwds):

        This only exists to give a better error message in case
        someone tries to subclass a special typing object (not a good idea).
        if (len(args) == 3 and
                isinstance(args[0], str) and
                isinstance(args[1], tuple)):
            # Close enough.
            raise TypeError(f"Cannot subclass {cls!r}")
        return super().__new__(cls)

    def __init__(self, name, doc):
        self._name = name
        self._doc = doc

    def __eq__(self, other):
        if not isinstance(other, _SpecialForm):
            return NotImplemented
        return self._name == other._name

    def __hash__(self):
        return hash((self._name,))

    def __repr__(self):
        return 'typing.' + self._name

    def __reduce__(self):
        return self._name

    def __call__(self, *args, **kwds):
        raise TypeError(f"Cannot instantiate {self!r}")

    def __instancecheck__(self, obj):
        raise TypeError(f"{self} cannot be used with isinstance()")

    def __subclasscheck__(self, cls):
        raise TypeError(f"{self} cannot be used with issubclass()")

    def __getitem__(self, parameters):
        if self._name in ('ClassVar', 'Final'):
            item = _type_check(parameters, f'{self._name} accepts only single type.')
            return _GenericAlias(self, (item,))
        if self._name == 'Union':
            if parameters == ():
                raise TypeError("Cannot take a Union of no types.")
            if not isinstance(parameters, tuple):
                parameters = (parameters,)
            msg = "Union[arg, ...]: each arg must be a type."
            parameters = tuple(_type_check(p, msg) for p in parameters)
            parameters = _remove_dups_flatten(parameters)
            if len(parameters) == 1:
                return parameters[0]
            return _GenericAlias(self, parameters)
        if self._name == 'Optional':
            arg = _type_check(parameters, "Optional[t] requires a single type.")
            return Union[arg, type(None)]
        if self._name == 'Literal':
            # There is no '_type_check' call because arguments to Literal[...] are
            # values, not types.
            return _GenericAlias(self, parameters)
        raise TypeError(f"{self} is not subscriptable")

Any = _SpecialForm('Any', doc=
    """Special type indicating an unconstrained type.

    - Any is compatible with every type.
    - Any assumed to have all methods.
    - All values assumed to be instances of Any.

    Note that all the above statements are true from the point of view of
    static type checkers. At runtime, Any should not be used with instance
    or class checks.

NoReturn = _SpecialForm('NoReturn', doc=
    """Special type indicating functions that never return.

      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.

ClassVar = _SpecialForm('ClassVar', doc=
    """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().

Final = _SpecialForm('Final', doc=
    """Special typing construct to indicate final names to type checkers.

    A final 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.

Union = _SpecialForm('Union', doc=
    """Union type; Union[X, Y] means either X or Y.

    To define a union, use e.g. Union[int, str].  Details:
    - The arguments must be types and there must be at least one.
    - None as an argument is a special case and is replaced by
    - Unions of unions are flattened, e.g.::

        Union[Union[int, str], float] == Union[int, str, float]

    - Unions of a single argument vanish, e.g.::

        Union[int] == int  # The constructor actually returns int

    - Redundant arguments are skipped, e.g.::

        Union[int, str, int] == Union[int, str]

    - When comparing unions, the argument order is ignored, e.g.::

        Union[int, str] == Union[str, int]

    - You cannot subclass or instantiate a union.
    - You can use Optional[X] as a shorthand for Union[X, None].

Optional = _SpecialForm('Optional', doc=
    """Optional type.

    Optional[X] is equivalent to Union[X, None].

Literal = _SpecialForm('Literal', doc=
    """Special typing form to define literal types (a.k.a. value types).

    This form can be used to indicate to type checkers that the corresponding
    variable or function parameter has a value equivalent to the provided
    literal (or one of several literals):

      def validate_simple(data: Any) -> Literal[True]:  # always returns True

      MODE = Literal['r', 'rb', 'w', 'wb']
      def open_helper(file: str, mode: MODE) -> str:

      open_helper('/some/path', 'r')  # Passes type check
      open_helper('/other/path', 'typo')  # Error in type checker

   Literal[...] cannot be subclassed. At runtime, an arbitrary value
   is allowed as type argument to Literal[...], but type checkers may
   impose restrictions.

class ForwardRef(_Final, _root=True):
    """Internal wrapper to hold a forward reference."""

    __slots__ = ('__forward_arg__', '__forward_code__',
                 '__forward_evaluated__', '__forward_value__',

    def __init__(self, arg, is_argument=True):
        if not isinstance(arg, str):
            raise TypeError(f"Forward reference must be a string -- got {arg!r}")
            code = compile(arg, '<string>', 'eval')
        except SyntaxError:
            raise SyntaxError(f"Forward reference must be an expression -- got {arg!r}")
        self.__forward_arg__ = arg
        self.__forward_code__ = code
        self.__forward_evaluated__ = False
        self.__forward_value__ = None
        self.__forward_is_argument__ = is_argument

    def _evaluate(self, globalns, localns):
        if not self.__forward_evaluated__ or localns is not globalns:
            if globalns is None and localns is None:
                globalns = localns = {}
            elif globalns is None:
                globalns = localns
            elif localns is None:
                localns = globalns
            self.__forward_value__ = _type_check(
                eval(self.__forward_code__, globalns, localns),
                "Forward references must evaluate to types.",
            self.__forward_evaluated__ = True
        return self.__forward_value__

    def __eq__(self, other):
        if not isinstance(other, ForwardRef):
            return NotImplemented
        if self.__forward_evaluated__ and other.__forward_evaluated__:
            return (self.__forward_arg__ == other.__forward_arg__ and
                    self.__forward_value__ == other.__forward_value__)
        return self.__forward_arg__ == other.__forward_arg__

    def __hash__(self):
        return hash(self.__forward_arg__)

    def __repr__(self):
        return f'ForwardRef({self.__forward_arg__!r})'

class TypeVar(_Final, _Immutable, _root=True):
    """Type variable.


      T = TypeVar('T')  # Can be anything
      A = TypeVar('A', str, bytes)  # Must be str or bytes

    Type variables exist primarily for the benefit of static type
    checkers.  They serve as the parameters for generic types as well
    as for generic function definitions.  See class Generic for more
    information on generic types.  Generic functions work as follows:

      def repeat(x: T, n: int) -> List[T]:
          '''Return a list containing n references to x.'''
          return [x]*n

      def longest(x: A, y: A) -> A:
          '''Return the longest of two strings.'''
          return x if len(x) >= len(y) else y

    The latter example's signature is essentially the overloading
    of (str, str) -> str and (bytes, bytes) -> bytes.  Also note
    that if the arguments are instances of some subclass of str,
    the return type is still plain str.

    At runtime, isinstance(x, T) and issubclass(C, T) will raise TypeError.

    Type variables defined with covariant=True or contravariant=True
    can be used to declare covariant or contravariant generic types.
    See PEP 484 for more details. By default generic types are invariant
    in all type variables.

    Type variables can be introspected. e.g.:

      T.__name__ == 'T'
      T.__constraints__ == ()
      T.__covariant__ == False
      T.__contravariant__ = False
      A.__constraints__ == (str, bytes)

    Note that only type variables defined in global scope can be pickled.

    __slots__ = ('__name__', '__bound__', '__constraints__',
                 '__covariant__', '__contravariant__')

    def __init__(self, name, *constraints, bound=None,
                 covariant=False, contravariant=False):
        self.__name__ = name
        if covariant and contravariant:
            raise ValueError("Bivariant types are not supported.")
        self.__covariant__ = bool(covariant)
        self.__contravariant__ = bool(contravariant)
        if constraints and bound is not None:
            raise TypeError("Constraints cannot be combined with bound=...")
        if constraints and len(constraints) == 1:
            raise TypeError("A single constraint is not allowed")
        msg = "TypeVar(name, constraint, ...): constraints must be types."
        self.__constraints__ = tuple(_type_check(t, msg) for t in constraints)
        if bound:
            self.__bound__ = _type_check(bound, "Bound must be a type.")
            self.__bound__ = None
            def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')  # for pickling
        except (AttributeError, ValueError):
            def_mod = None
        if def_mod != 'typing':
            self.__module__ = def_mod

    def __repr__(self):
        if self.__covariant__:
            prefix = '+'
        elif self.__contravariant__:
            prefix = '-'
            prefix = '~'
        return prefix + self.__name__

    def __reduce__(self):
        return self.__name__

# Special typing constructs Union, Optional, Generic, Callable and Tuple
# use three special attributes for internal bookkeeping of generic types:
# * __parameters__ is a tuple of unique free type parameters of a generic
#   type, for example, Dict[T, T].__parameters__ == (T,);
# * __origin__ keeps a reference to a type that was subscripted,
#   e.g., Union[T, int].__origin__ == Union, or the non-generic version of
#   the type.
# * __args__ is a tuple of all arguments used in subscripting,
#   e.g., Dict[T, int].__args__ == (T, int).

# Mapping from non-generic type names that have a generic alias in typing
# but with a different name.
_normalize_alias = {'list': 'List',
                    'tuple': 'Tuple',
                    'dict': 'Dict',
                    'set': 'Set',
                    'frozenset': 'FrozenSet',
                    'deque': 'Deque',
                    'defaultdict': 'DefaultDict',
                    'type': 'Type',
                    'Set': 'AbstractSet'}

def _is_dunder(attr):
    return attr.startswith('__') and attr.endswith('__')

class _GenericAlias(_Final, _root=True):
    """The central part of internal API.

    This represents a generic version of type 'origin' with type arguments 'params'.
    There are two kind of these aliases: user defined and special. The special ones
    are wrappers around builtin collections and ABCs in These must
    have 'name' always set. If 'inst' is False, then the alias can't be instantiated,
    this is used by e.g. typing.List and typing.Dict.
    def __init__(self, origin, params, *, inst=True, special=False, name=None):
        self._inst = inst
        self._special = special
        if special and name is None:
            orig_name = origin.__name__
            name = _normalize_alias.get(orig_name, orig_name)
        self._name = name
        if not isinstance(params, tuple):
            params = (params,)
        self.__origin__ = origin
        self.__args__ = tuple(... if a is _TypingEllipsis else
                              () if a is _TypingEmpty else
                              a for a in params)
        self.__parameters__ = _collect_type_vars(params)
        self.__slots__ = None  # This is not documented.
        if not name:
            self.__module__ = origin.__module__

    def __getitem__(self, params):
        if self.__origin__ in (Generic, Protocol):
            # Can't subscript Generic[...] or Protocol[...].
            raise TypeError(f"Cannot subscript already-subscripted {self}")
        if not isinstance(params, tuple):
            params = (params,)
        msg = "Parameters to generic types must be types."
        params = tuple(_type_check(p, msg) for p in params)
        _check_generic(self, params)
        return _subs_tvars(self, self.__parameters__, params)

    def copy_with(self, params):
        # We don't copy self._special.
        return _GenericAlias(self.__origin__, params, name=self._name, inst=self._inst)

    def __repr__(self):
        if (self._name != 'Callable' or
                len(self.__args__) == 2 and self.__args__[0] is Ellipsis):
            if self._name:
                name = 'typing.' + self._name
                name = _type_repr(self.__origin__)
            if not self._special:
                args = f'[{", ".join([_type_repr(a) for a in self.__args__])}]'
                args = ''
            return (f'{name}{args}')
        if self._special:
            return 'typing.Callable'
        return (f'typing.Callable'
                f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], '

    def __eq__(self, other):
        if not isinstance(other, _GenericAlias):
            return NotImplemented
        if self.__origin__ != other.__origin__:
            return False
        if self.__origin__ is Union and other.__origin__ is Union:
            return frozenset(self.__args__) == frozenset(other.__args__)
        return self.__args__ == other.__args__

    def __hash__(self):
        if self.__origin__ is Union:
            return hash((Union, frozenset(self.__args__)))
        return hash((self.__origin__, self.__args__))

    def __call__(self, *args, **kwargs):
        if not self._inst:
            raise TypeError(f"Type {self._name} cannot be instantiated; "
                            f"use {self._name.lower()}() instead")
        result = self.__origin__(*args, **kwargs)
            result.__orig_class__ = self
        except AttributeError:
        return result

    def __mro_entries__(self, bases):
        if self._name:  # generic version of an ABC or built-in class
            res = []
            if self.__origin__ not in bases:
            i = bases.index(self)
            if not any(isinstance(b, _GenericAlias) or issubclass(b, Generic)
                       for b in bases[i+1:]):
            return tuple(res)
        if self.__origin__ is Generic:
            if Protocol in bases:
                return ()
            i = bases.index(self)
            for b in bases[i+1:]:
                if isinstance(b, _GenericAlias) and b is not self:
                    return ()
        return (self.__origin__,)

    def __getattr__(self, attr):
        # We are careful for copy and pickle.
        # Also for simplicity we just don't relay all dunder names
        if '__origin__' in self.__dict__ and not _is_dunder(attr):
            return getattr(self.__origin__, attr)
        raise AttributeError(attr)

    def __setattr__(self, attr, val):
        if _is_dunder(attr) or attr in ('_name', '_inst', '_special'):
            super().__setattr__(attr, val)
            setattr(self.__origin__, attr, val)

    def __instancecheck__(self, obj):
        return self.__subclasscheck__(type(obj))

    def __subclasscheck__(self, cls):
        if self._special:
            if not isinstance(cls, _GenericAlias):
                return issubclass(cls, self.__origin__)
            if cls._special:
                return issubclass(cls.__origin__, self.__origin__)
        raise TypeError("Subscripted generics cannot be used with"
                        " class and instance checks")

    def __reduce__(self):
        if self._special:
            return self._name

        if self._name:
            origin = globals()[self._name]
            origin = self.__origin__
        if (origin is Callable and
            not (len(self.__args__) == 2 and self.__args__[0] is Ellipsis)):
            args = list(self.__args__[:-1]), self.__args__[-1]
            args = tuple(self.__args__)
            if len(args) == 1 and not isinstance(args[0], tuple):
                args, = args
        return operator.getitem, (origin, args)

class _VariadicGenericAlias(_GenericAlias, _root=True):
    """Same as _GenericAlias above but for variadic aliases. Currently,
    this is used only by special internal aliases: Tuple and Callable.
    def __getitem__(self, params):
        if self._name != 'Callable' or not self._special:
            return self.__getitem_inner__(params)
        if not isinstance(params, tuple) or len(params) != 2:
            raise TypeError("Callable must be used as "
                            "Callable[[arg, ...], result].")
        args, result = params
        if args is Ellipsis:
            params = (Ellipsis, result)
            if not isinstance(args, list):
                raise TypeError(f"Callable[args, result]: args must be a list."
                                f" Got {args}")
            params = (tuple(args), result)
        return self.__getitem_inner__(params)

    def __getitem_inner__(self, params):
        if self.__origin__ is tuple and self._special:
            if params == ():
                return self.copy_with((_TypingEmpty,))
            if not isinstance(params, tuple):
                params = (params,)
            if len(params) == 2 and params[1] is ...:
                msg = "Tuple[t, ...]: t must be a type."
                p = _type_check(params[0], msg)
                return self.copy_with((p, _TypingEllipsis))
            msg = "Tuple[t0, t1, ...]: each t must be a type."
            params = tuple(_type_check(p, msg) for p in params)
            return self.copy_with(params)
        if self.__origin__ is and self._special:
            args, result = params
            msg = "Callable[args, result]: result must be a type."
            result = _type_check(result, msg)
            if args is Ellipsis:
                return self.copy_with((_TypingEllipsis, result))
            msg = "Callable[[arg, ...], result]: each arg must be a type."
            args = tuple(_type_check(arg, msg) for arg in args)
            params = args + (result,)
            return self.copy_with(params)
        return super().__getitem__(params)

class Generic:
    """Abstract base class for generic types.

    A generic type is typically declared by inheriting from
    this class parameterized with one or more type variables.
    For example, a generic mapping type might be defined as::

      class Mapping(Generic[KT, VT]):
          def __getitem__(self, key: KT) -> VT:
          # Etc.

    This class can then be used as follows::

      def lookup_name(mapping: Mapping[KT, VT], key: KT, default: VT) -> VT:
              return mapping[key]
          except KeyError:
              return default
    __slots__ = ()
    _is_protocol = False

    def __new__(cls, *args, **kwds):
        if cls in (Generic, Protocol):
            raise TypeError(f"Type {cls.__name__} cannot be instantiated; "
                            "it can be used only as a base class")
        if super().__new__ is object.__new__ and cls.__init__ is not object.__init__:
            obj = super().__new__(cls)
            obj = super().__new__(cls, *args, **kwds)
        return obj

    def __class_getitem__(cls, params):
        if not isinstance(params, tuple):
            params = (params,)
        if not params and cls is not Tuple:
            raise TypeError(
                f"Parameter list to {cls.__qualname__}[...] cannot be empty")
        msg = "Parameters to generic types must be types."
        params = tuple(_type_check(p, msg) for p in params)
        if cls in (Generic, Protocol):
            # Generic and Protocol can only be subscripted with unique type variables.
            if not all(isinstance(p, TypeVar) for p in params):
                raise TypeError(
                    f"Parameters to {cls.__name__}[...] must all be type variables")
            if len(set(params)) != len(params):
                raise TypeError(
                    f"Parameters to {cls.__name__}[...] must all be unique")
            # Subscripting a regular Generic subclass.
            _check_generic(cls, params)
        return _GenericAlias(cls, params)

    def __init_subclass__(cls, *args, **kwargs):
        super().__init_subclass__(*args, **kwargs)
        tvars = []
        if '__orig_bases__' in cls.__dict__:
            error = Generic in cls.__orig_bases__
            error = Generic in cls.__bases__ and cls.__name__ != 'Protocol'
        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].
            # 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[...].
            gvars = None
            for base in cls.__orig_bases__:
                if (isinstance(base, _GenericAlias) and
                        base.__origin__ is Generic):
                    if gvars is not None:
                        raise TypeError(
                            "Cannot inherit from Generic[...] multiple types.")
                    gvars = base.__parameters__
            if gvars is not None:
                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(f"Some type variables ({s_vars}) are"
                                    f" not listed in Generic[{s_args}]")
                tvars = gvars
        cls.__parameters__ = tuple(tvars)

class _TypingEmpty:
    """Internal placeholder for () or []. Used by TupleMeta and CallableMeta
    to allow empty list/tuple in specific places, without allowing them
    to sneak in where prohibited.

class _TypingEllipsis:
    """Internal placeholder for ... (ellipsis)."""

_TYPING_INTERNALS = ['__parameters__', '__orig_bases__',  '__orig_class__',
                     '_is_protocol', '_is_runtime_protocol']

_SPECIAL_NAMES = ['__abstractmethods__', '__annotations__', '__dict__', '__doc__',
                  '__init__', '__module__', '__new__', '__slots__',
                  '__subclasshook__', '__weakref__']

# These special attributes will be not collected as protocol members.

def _get_protocol_attrs(cls):
    """Collect protocol members from a protocol class objects.

    This includes names actually defined in the class dictionary, as well
    as names that appear in annotations. Special names (above) are skipped.
    attrs = set()
    for base in cls.__mro__[:-1]:  # without object
        if base.__name__ in ('Protocol', 'Generic'):
        annotations = getattr(base, '__annotations__', {})
        for attr in list(base.__dict__.keys()) + list(annotations.keys()):
            if not attr.startswith('_abc_') and attr not in EXCLUDED_ATTRIBUTES:
    return attrs

def _is_callable_members_only(cls):
    # PEP 544 prohibits using issubclass() with protocols that have non-method members.
    return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls))

def _no_init(self, *args, **kwargs):
    if type(self)._is_protocol:
        raise TypeError('Protocols cannot be instantiated')

def _allow_reckless_class_cheks():
    """Allow instnance and class checks for special stdlib modules.

    The abc and functools modules indiscriminately call isinstance() and
    issubclass() on the whole MRO of a user class, which may contain protocols.
        return sys._getframe(3).f_globals['__name__'] in ['abc', 'functools']
    except (AttributeError, ValueError):  # For platforms without _getframe().
        return True

    '': [
        'Callable', 'Awaitable', 'Iterable', 'Iterator', 'AsyncIterable',
        'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',
    'contextlib': ['AbstractContextManager', 'AbstractAsyncContextManager'],

class _ProtocolMeta(ABCMeta):
    # This metaclass is really 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
                    # All *methods* can be blocked by setting them to None.
                    (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(Generic, 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.runtime_checkable act as simple-minded runtime protocols that check
    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
    _is_runtime_protocol = False

    def __init_subclass__(cls, *args, **kwargs):
        super().__init_subclass__(*args, **kwargs)

        # Determine if this is a protocol or a concrete subclass.
        if not cls.__dict__.get('_is_protocol', False):
            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', False):
                return NotImplemented

            # First, perform various sanity checks.
            if not getattr(cls, '_is_runtime_protocol', False):
                if _allow_reckless_class_cheks():
                    return NotImplemented
                raise TypeError("Instance and class checks can only be used with"
                                " @runtime_checkable protocols")
            if not _is_callable_members_only(cls):
                if _allow_reckless_class_cheks():
                    return NotImplemented
                raise TypeError("Protocols with non-method members"
                                " don't support issubclass()")
            if not isinstance(other, type):
                # Same error message as for issubclass(1, int).
                raise TypeError('issubclass() arg 1 must be a class')

            # Second, perform the actual structural compatibility check.
            for attr in _get_protocol_attrs(cls):
                for base in other.__mro__:
                    # Check if the members appears in the class dictionary...
                    if attr in base.__dict__:
                        if base.__dict__[attr] is None:
                            return NotImplemented

                    # ...or in annotations, if it is a sub-protocol.
                    annotations = getattr(base, '__annotations__', {})
                    if (isinstance(annotations, and
                            attr in annotations and
                            issubclass(other, Generic) and other._is_protocol):
                    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:

        # ... otherwise check consistency of bases, and prohibit instantiation.
        for base in cls.__bases__:
            if not (base in (object, Generic) or
                    base.__module__ in _PROTO_WHITELIST and
                    base.__name__ in _PROTO_WHITELIST[base.__module__] or
                    issubclass(base, Generic) and base._is_protocol):
                raise TypeError('Protocols can only inherit from other'
                                ' protocols, got %r' % base)
        cls.__init__ = _no_init

def runtime_checkable(cls):
    """Mark a protocol class as a runtime protocol.

    Such protocol 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
    one trick ponies in such as Iterable.
    For example::

        class Closable(Protocol):
            def close(self): ...

        assert isinstance(open('/some/file'), Closable)

    Warning: this will check only the presence of the required methods,
    not their type signatures!
    if not issubclass(cls, Generic) 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

def cast(typ, val):
    """Cast a value to a type.

    This returns the value unchanged.  To the type checker this
    signals that the return value has the designated type, but at
    runtime we intentionally don't check anything (we want this
    to be as fast as possible).
    return val

def _get_defaults(func):
    """Internal helper to extract the default arguments, by name."""
        code = func.__code__
    except AttributeError:
        # Some built-in functions don't have __code__, __defaults__, etc.
        return {}
    pos_count = code.co_argcount
    arg_names = code.co_varnames
    arg_names = arg_names[:pos_count]
    defaults = func.__defaults__ or ()
    kwdefaults = func.__kwdefaults__
    res = dict(kwdefaults) if kwdefaults else {}
    pos_offset = pos_count - len(defaults)
    for name, value in zip(arg_names[pos_offset:], defaults):
        assert name not in res
        res[name] = value
    return res

_allowed_types = (types.FunctionType, types.BuiltinFunctionType,
                  types.MethodType, types.ModuleType,
                  WrapperDescriptorType, MethodWrapperType, MethodDescriptorType)

def get_type_hints(obj, globalns=None, localns=None):
    """Return type hints for an object.

    This is often the same as obj.__annotations__, but it handles
    forward references encoded as string literals, and if necessary
    adds Optional[t] if a default value equal to None is set.

    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

    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

    - If two dict arguments are passed, they specify globals and
      locals, respectively.

    if getattr(obj, '__no_type_check__', None):
        return {}
    # Classes require a special treatment.
    if isinstance(obj, type):
        hints = {}
        for base in reversed(obj.__mro__):
            if globalns is None:
                base_globals = sys.modules[base.__module__].__dict__
                base_globals = globalns
            ann = base.__dict__.get('__annotations__', {})
            for name, value in ann.items():
                if value is None:
                    value = type(None)
                if isinstance(value, str):
                    value = ForwardRef(value, is_argument=False)
                value = _eval_type(value, base_globals, localns)
                hints[name] = value
        return hints

    if globalns is None:
        if isinstance(obj, types.ModuleType):
            globalns = obj.__dict__
            nsobj = obj
            # Find globalns for the unwrapped object.
            while hasattr(nsobj, '__wrapped__'):
                nsobj = nsobj.__wrapped__
            globalns = getattr(nsobj, '__globals__', {})
        if localns is None:
            localns = globalns
    elif localns is None:
        localns = globalns
    hints = getattr(obj, '__annotations__', None)
    if hints is None:
        # Return empty annotations for something that _could_ have them.
        if isinstance(obj, _allowed_types):
            return {}
            raise TypeError('{!r} is not a module, class, method, '
                            'or function.'.format(obj))
    defaults = _get_defaults(obj)
    hints = dict(hints)
    for name, value in hints.items():
        if value is None:
            value = type(None)
        if isinstance(value, str):
            value = ForwardRef(value)
        value = _eval_type(value, globalns, localns)
        if name in defaults and defaults[name] is None:
            value = Optional[value]
        hints[name] = value
    return hints

def get_origin(tp):
    """Get the unsubscripted version of a type.

    This supports generic types, Callable, Tuple, Union, Literal, Final and ClassVar.
    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, _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.
        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, _GenericAlias) and not tp._special:
        res = tp.__args__
        if get_origin(tp) is and res[0] is not Ellipsis:
            res = (list(res[:-1]), res[-1])
        return res
    return ()

def no_type_check(arg):
    """Decorator to indicate that annotations are not type hints.

    The argument must be a class or function; if it is a class, it
    applies recursively to all methods and classes defined in that class
    (but not to methods defined in its superclasses or subclasses).

    This mutates the function(s) or class(es) in place.
    if isinstance(arg, type):
        arg_attrs = arg.__dict__.copy()
        for attr, val in arg.__dict__.items():
            if val in arg.__bases__ + (arg,):
        for obj in arg_attrs.values():
            if isinstance(obj, types.FunctionType):
                obj.__no_type_check__ = True
            if isinstance(obj, type):
        arg.__no_type_check__ = True
    except TypeError:  # built-in classes
    return arg

def no_type_check_decorator(decorator):
    """Decorator to give another decorator the @no_type_check effect.

    This wraps the decorator with something that wraps the decorated
    function in @no_type_check.

    def wrapped_decorator(*args, **kwds):
        func = decorator(*args, **kwds)
        func = no_type_check(func)
        return func

    return wrapped_decorator

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:

      def utf8(value: None) -> None: ...
      def utf8(value: bytes) -> bytes: ...
      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:

      def utf8(value: None) -> None: ...
      def utf8(value: bytes) -> bytes: ...
      def utf8(value: str) -> bytes: ...
      def utf8(value):
          # implementation goes here
    return _overload_dummy

def final(f):
    """A decorator to indicate final methods and final classes.

    Use this decorator to indicate to type checkers that the decorated
    method cannot be overridden, and decorated class cannot be subclassed.
    For example:

      class Base:
          def done(self) -> None:
      class Sub(Base):
          def done(self) -> None:  # Error reported by type checker

      class Leaf:
      class Other(Leaf):  # Error reported by type checker

    There is no runtime checking of these properties.
    return f

# Some unconstrained type variables.  These are used by the container types.
# (These are not for export.)
T = TypeVar('T')  # Any type.
KT = TypeVar('KT')  # Key type.
VT = TypeVar('VT')  # Value type.
T_co = TypeVar('T_co', covariant=True)  # Any type covariant containers.
V_co = TypeVar('V_co', covariant=True)  # Any type covariant containers.
VT_co = TypeVar('VT_co', covariant=True)  # Value type covariant containers.
T_contra = TypeVar('T_contra', contravariant=True)  # Ditto contravariant.
# Internal type variable used for Type[].
CT_co = TypeVar('CT_co', covariant=True, bound=type)

# A useful type variable with constraints.  This represents string types.
# (This one *is* for export!)
AnyStr = TypeVar('AnyStr', bytes, str)

# Various ABCs mimicking those in
def _alias(origin, params, inst=True):
    return _GenericAlias(origin, params, special=True, inst=inst)

Hashable = _alias(, ())  # Not generic.
Awaitable = _alias(, T_co)
Coroutine = _alias(, (T_co, T_contra, V_co))
AsyncIterable = _alias(, T_co)
AsyncIterator = _alias(, T_co)
Iterable = _alias(, T_co)
Iterator = _alias(, T_co)
Reversible = _alias(, T_co)
Sized = _alias(, ())  # Not generic.
Container = _alias(, T_co)
Collection = _alias(, T_co)
Callable = _VariadicGenericAlias(, (), special=True)
Callable.__doc__ = \
    """Callable type; Callable[[int], str] is a function of (int) -> str.

    The subscription syntax must always be used with exactly two
    values: the argument list and the return type.  The argument list
    must be a list of types or ellipsis; the return type must be a single type.

    There is no syntax to indicate optional or keyword arguments,
    such function types are rarely used as callback types.
AbstractSet = _alias(, T_co)
MutableSet = _alias(, T)
# NOTE: Mapping is only covariant in the value type.
Mapping = _alias(, (KT, VT_co))
MutableMapping = _alias(, (KT, VT))
Sequence = _alias(, T_co)
MutableSequence = _alias(, T)
ByteString = _alias(, ())  # Not generic
Tuple = _VariadicGenericAlias(tuple, (), inst=False, special=True)
Tuple.__doc__ = \
    """Tuple type; Tuple[X, Y] is the cross-product type of X and Y.

    Example: Tuple[T1, T2] is a tuple of two elements corresponding
    to type variables T1 and T2.  Tuple[int, float, str] is a tuple
    of an int, a float and a string.

    To specify a variable-length tuple of homogeneous type, use Tuple[T, ...].
List = _alias(list, T, inst=False)
Deque = _alias(collections.deque, T)
Set = _alias(set, T, inst=False)
FrozenSet = _alias(frozenset, T_co, inst=False)
MappingView = _alias(, T_co)
KeysView = _alias(, KT)
ItemsView = _alias(, (KT, VT_co))
ValuesView = _alias(, VT_co)
ContextManager = _alias(contextlib.AbstractContextManager, T_co)
AsyncContextManager = _alias(contextlib.AbstractAsyncContextManager, T_co)
Dict = _alias(dict, (KT, VT), inst=False)
DefaultDict = _alias(collections.defaultdict, (KT, VT))
OrderedDict = _alias(collections.OrderedDict, (KT, VT))
Counter = _alias(collections.Counter, T)
ChainMap = _alias(collections.ChainMap, (KT, VT))
Generator = _alias(, (T_co, T_contra, V_co))
AsyncGenerator = _alias(, (T_co, T_contra))
Type = _alias(type, CT_co, inst=False)
Type.__doc__ = \
    """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.

class SupportsInt(Protocol):
    """An ABC with one abstract method __int__."""
    __slots__ = ()

    def __int__(self) -> int:

class SupportsFloat(Protocol):
    """An ABC with one abstract method __float__."""
    __slots__ = ()

    def __float__(self) -> float:

class SupportsComplex(Protocol):
    """An ABC with one abstract method __complex__."""
    __slots__ = ()

    def __complex__(self) -> complex:

class SupportsBytes(Protocol):
    """An ABC with one abstract method __bytes__."""
    __slots__ = ()

    def __bytes__(self) -> bytes:

class SupportsIndex(Protocol):
    """An ABC with one abstract method __index__."""
    __slots__ = ()

    def __index__(self) -> int:

class SupportsAbs(Protocol[T_co]):
    """An ABC with one abstract method __abs__ that is covariant in its return type."""
    __slots__ = ()

    def __abs__(self) -> T_co:

class SupportsRound(Protocol[T_co]):
    """An ABC with one abstract method __round__ that is covariant in its return type."""
    __slots__ = ()

    def __round__(self, ndigits: int = 0) -> T_co:

def _make_nmtuple(name, types):
    msg = "NamedTuple('Name', [(f0, t0), (f1, t1), ...]); each t must be a type"
    types = [(n, _type_check(t, msg)) for n, t in types]
    nm_tpl = collections.namedtuple(name, [n for n, t in types])
    # Prior to PEP 526, only _field_types attribute was assigned.
    # Now __annotations__ are used and _field_types is deprecated (remove in 3.9)
    nm_tpl.__annotations__ = nm_tpl._field_types = dict(types)
        nm_tpl.__module__ = sys._getframe(2).f_globals.get('__name__', '__main__')
    except (AttributeError, ValueError):
    return nm_tpl

# attributes prohibited to set in NamedTuple class syntax
_prohibited = ('__new__', '__init__', '__slots__', '__getnewargs__',
               '_fields', '_field_defaults', '_field_types',
               '_make', '_replace', '_asdict', '_source')

_special = ('__module__', '__name__', '__annotations__')

class NamedTupleMeta(type):

    def __new__(cls, typename, bases, ns):
        if ns.get('_root', False):
            return super().__new__(cls, typename, bases, ns)
        types = ns.get('__annotations__', {})
        nm_tpl = _make_nmtuple(typename, types.items())
        defaults = []
        defaults_dict = {}
        for field_name in types:
            if field_name in ns:
                default_value = ns[field_name]
                defaults_dict[field_name] = default_value
            elif defaults:
                raise TypeError("Non-default namedtuple field {field_name} cannot "
                                "follow default field(s) {default_names}"
                                        default_names=', '.join(defaults_dict.keys())))
        nm_tpl.__new__.__annotations__ = dict(types)
        nm_tpl.__new__.__defaults__ = tuple(defaults)
        nm_tpl._field_defaults = defaults_dict
        # update from user namespace without overriding special namedtuple attributes
        for key in ns:
            if key in _prohibited:
                raise AttributeError("Cannot overwrite NamedTuple attribute " + key)
            elif key not in _special and key not in nm_tpl._fields:
                setattr(nm_tpl, key, ns[key])
        return nm_tpl

class NamedTuple(metaclass=NamedTupleMeta):
    """Typed version of namedtuple.

    Usage in Python versions >= 3.6::

        class Employee(NamedTuple):
            name: str
            id: int

    This is equivalent to::

        Employee = collections.namedtuple('Employee', ['name', 'id'])

    The resulting class has an extra __annotations__ attribute, giving a
    dict that maps field names to types.  (The field names are also in
    the _fields attribute, which is part of the namedtuple API.)
    Alternative equivalent keyword syntax is also accepted::

        Employee = NamedTuple('Employee', name=str, id=int)

    In Python versions <= 3.5 use::

        Employee = NamedTuple('Employee', [('name', str), ('id', int)])
    _root = True

    def __new__(*args, **kwargs):
        if not args:
            raise TypeError('NamedTuple.__new__(): not enough arguments')
        cls, *args = args  # allow the "cls" keyword be passed
        if args:
            typename, *args = args # 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)
            raise TypeError("NamedTuple.__new__() missing 1 required positional "
                            "argument: 'typename'")
        if args:
                fields, = args # allow the "fields" keyword be passed
            except ValueError:
                raise TypeError(f'NamedTuple.__new__() takes from 2 to 3 '
                                f'positional arguments but {len(args) + 2} '
                                f'were given') from None
        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)
            fields = None

        if fields is None:
            fields = kwargs.items()
        elif kwargs:
            raise TypeError("Either list of fields or keywords"
                            " can be provided to NamedTuple, not both")
        return _make_nmtuple(typename, fields)
    __new__.__text_signature__ = '($cls, typename, fields=None, /, **kwargs)'

def _dict_new(cls, /, *args, **kwargs):
    return dict(*args, **kwargs)

def _typeddict_new(cls, typename, fields=None, /, *, total=True, **kwargs):
    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}
        # Setting correct module is necessary to make typed dict classes pickleable.
        ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
    except (AttributeError, ValueError):

    return _TypedDictMeta(typename, (), ns)

def _check_fails(cls, other):
    # Typed dicts are only for static structural subtyping.
    raise TypeError('TypedDict does not support instance and class checks')

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 syntax forms 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)

        anns = ns.get('__annotations__', {})
        msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
        anns = {n: _type_check(tp, msg) for n, tp in anns.items()}
        for base in bases:
            anns.update(base.__dict__.get('__annotations__', {}))
        tp_dict.__annotations__ = anns
        if not hasattr(tp_dict, '__total__'):
            tp_dict.__total__ = total
        return tp_dict

    __instancecheck__ = __subclasscheck__ = _check_fails

class TypedDict(dict, metaclass=_TypedDictMeta):
    """A simple typed namespace. 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, where each key is
    associated with a value of a consistent type. This expectation
    is not checked at runtime but is only enforced by type checkers.

        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 Point2D.__annotations__. TypedDict
    supports two additional equivalent forms::

        Point2D = TypedDict('Point2D', x=int, y=int, label=str)
        Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})

    By default, all keys must be present in a TypedDict. It is possible
    to override this by specifying totality.

        class point2D(TypedDict, total=False):
            x: int
            y: int

    This means that a point2D TypedDict can have any of the keys omitted.A type
    checker is only expected to support a literal False or True as the value of
    the total argument. True is the default, and makes all items defined in the
    class body be required.

    The class syntax is only supported in Python 3.6+, while two other
    syntax forms work for Python 2.7 and 3.2+

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

# Python-version-specific alias (Python 2: unicode; Python 3: str)
Text = str

# Constant that's True when type checking, but False here.

class IO(Generic[AnyStr]):
    """Generic base class for TextIO and BinaryIO.

    This is an abstract, generic version of the return of open().

    NOTE: This does not distinguish between the different possible
    classes (text vs. binary, read vs. write vs. read/write,
    append-only, unbuffered).  The TextIO and BinaryIO subclasses
    below capture the distinctions between text vs. binary, which is
    pervasive in the interface; however we currently do not offer a
    way to track the other distinctions in the type system.

    __slots__ = ()

    def mode(self) -> str:

    def name(self) -> str:

    def close(self) -> None:

    def closed(self) -> bool:

    def fileno(self) -> int:

    def flush(self) -> None:

    def isatty(self) -> bool:

    def read(self, n: int = -1) -> AnyStr:

    def readable(self) -> bool:

    def readline(self, limit: int = -1) -> AnyStr:

    def readlines(self, hint: int = -1) -> List[AnyStr]:

    def seek(self, offset: int, whence: int = 0) -> int:

    def seekable(self) -> bool:

    def tell(self) -> int:

    def truncate(self, size: int = None) -> int:

    def writable(self) -> bool:

    def write(self, s: AnyStr) -> int:

    def writelines(self, lines: List[AnyStr]) -> None:

    def __enter__(self) -> 'IO[AnyStr]':

    def __exit__(self, type, value, traceback) -> None:

class BinaryIO(IO[bytes]):
    """Typed version of the return of open() in binary mode."""

    __slots__ = ()

    def write(self, s: Union[bytes, bytearray]) -> int:

    def __enter__(self) -> 'BinaryIO':

class TextIO(IO[str]):
    """Typed version of the return of open() in text mode."""

    __slots__ = ()

    def buffer(self) -> BinaryIO:

    def encoding(self) -> str:

    def errors(self) -> Optional[str]:

    def line_buffering(self) -> bool:

    def newlines(self) -> Any:

    def __enter__(self) -> 'TextIO':

class io:
    """Wrapper namespace for IO generic classes."""

    __all__ = ['IO', 'TextIO', 'BinaryIO']
    IO = IO
    TextIO = TextIO
    BinaryIO = BinaryIO

io.__name__ = __name__ + '.io'
sys.modules[io.__name__] = io

Pattern = _alias(stdlib_re.Pattern, AnyStr)
Match = _alias(stdlib_re.Match, AnyStr)

class re:
    """Wrapper namespace for re type aliases."""

    __all__ = ['Pattern', 'Match']
    Pattern = Pattern
    Match = Match

re.__name__ = __name__ + '.re'
sys.modules[re.__name__] = re