mirror of https://github.com/python/cpython
1644 lines
52 KiB
Python
1644 lines
52 KiB
Python
# TODO:
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# - Generic[T, T] is invalid
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# - Look for TODO below
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# TODO nits:
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# Get rid of asserts that are the caller's fault.
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# Docstrings (e.g. ABCs).
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import abc
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from abc import abstractmethod, abstractproperty
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import collections
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import functools
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import re as stdlib_re # Avoid confusion with the re we export.
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import sys
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import types
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try:
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import collections.abc as collections_abc
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except ImportError:
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import collections as collections_abc # Fallback for PY3.2.
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# Please keep __all__ alphabetized within each category.
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__all__ = [
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# Super-special typing primitives.
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'Any',
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'Callable',
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'Generic',
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'Optional',
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'TypeVar',
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'Union',
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'Tuple',
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# ABCs (from collections.abc).
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'AbstractSet', # collections.abc.Set.
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'ByteString',
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'Container',
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'Hashable',
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'ItemsView',
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'Iterable',
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'Iterator',
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'KeysView',
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'Mapping',
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'MappingView',
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'MutableMapping',
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'MutableSequence',
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'MutableSet',
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'Sequence',
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'Sized',
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'ValuesView',
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# Structural checks, a.k.a. protocols.
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'Reversible',
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'SupportsAbs',
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'SupportsFloat',
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'SupportsInt',
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'SupportsRound',
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# Concrete collection types.
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'Dict',
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'List',
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'Set',
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'NamedTuple', # Not really a type.
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'Generator',
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# One-off things.
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'AnyStr',
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'cast',
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'get_type_hints',
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'no_type_check',
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'no_type_check_decorator',
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'overload',
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# Submodules.
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'io',
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're',
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]
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def _qualname(x):
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if sys.version_info[:2] >= (3, 3):
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return x.__qualname__
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else:
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# Fall back to just name.
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return x.__name__
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class TypingMeta(type):
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"""Metaclass for every type defined below.
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This overrides __new__() to require an extra keyword parameter
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'_root', which serves as a guard against naive subclassing of the
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typing classes. Any legitimate class defined using a metaclass
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derived from TypingMeta (including internal subclasses created by
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e.g. Union[X, Y]) must pass _root=True.
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This also defines a dummy constructor (all the work is done in
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__new__) and a nicer repr().
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"""
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_is_protocol = False
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def __new__(cls, name, bases, namespace, *, _root=False):
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if not _root:
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raise TypeError("Cannot subclass %s" %
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(', '.join(map(_type_repr, bases)) or '()'))
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return super().__new__(cls, name, bases, namespace)
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def __init__(self, *args, **kwds):
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pass
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def _eval_type(self, globalns, localns):
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"""Override this in subclasses to interpret forward references.
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For example, Union['C'] is internally stored as
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Union[_ForwardRef('C')], which should evaluate to _Union[C],
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where C is an object found in globalns or localns (searching
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localns first, of course).
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"""
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return self
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def _has_type_var(self):
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return False
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def __repr__(self):
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return '%s.%s' % (self.__module__, _qualname(self))
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class Final:
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"""Mix-in class to prevent instantiation."""
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__slots__ = ()
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def __new__(self, *args, **kwds):
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raise TypeError("Cannot instantiate %r" % self.__class__)
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class _ForwardRef(TypingMeta):
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"""Wrapper to hold a forward reference."""
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def __new__(cls, arg):
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if not isinstance(arg, str):
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raise TypeError('ForwardRef must be a string -- got %r' % (arg,))
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try:
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code = compile(arg, '<string>', 'eval')
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except SyntaxError:
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raise SyntaxError('ForwardRef must be an expression -- got %r' %
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(arg,))
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self = super().__new__(cls, arg, (), {}, _root=True)
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self.__forward_arg__ = arg
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self.__forward_code__ = code
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self.__forward_evaluated__ = False
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self.__forward_value__ = None
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typing_globals = globals()
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frame = sys._getframe(1)
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while frame is not None and frame.f_globals is typing_globals:
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frame = frame.f_back
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assert frame is not None
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self.__forward_frame__ = frame
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return self
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def _eval_type(self, globalns, localns):
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if not isinstance(localns, dict):
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raise TypeError('ForwardRef localns must be a dict -- got %r' %
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(localns,))
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if not isinstance(globalns, dict):
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raise TypeError('ForwardRef globalns must be a dict -- got %r' %
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(globalns,))
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if not self.__forward_evaluated__:
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if globalns is None and localns is None:
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globalns = localns = {}
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elif globalns is None:
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globalns = localns
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elif localns is None:
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localns = globalns
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self.__forward_value__ = _type_check(
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eval(self.__forward_code__, globalns, localns),
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"Forward references must evaluate to types.")
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self.__forward_evaluated__ = True
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return self.__forward_value__
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def __instancecheck__(self, obj):
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raise TypeError("Forward references cannot be used with isinstance().")
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def __subclasscheck__(self, cls):
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if not self.__forward_evaluated__:
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globalns = self.__forward_frame__.f_globals
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localns = self.__forward_frame__.f_locals
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try:
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self._eval_type(globalns, localns)
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except NameError:
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return False # Too early.
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return issubclass(cls, self.__forward_value__)
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def __repr__(self):
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return '_ForwardRef(%r)' % (self.__forward_arg__,)
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class _TypeAlias:
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"""Internal helper class for defining generic variants of concrete types.
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Note that this is not a type; let's call it a pseudo-type. It can
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be used in instance and subclass checks, e.g. isinstance(m, Match)
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or issubclass(type(m), Match). However, it cannot be itself the
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target of an issubclass() call; e.g. issubclass(Match, C) (for
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some arbitrary class C) raises TypeError rather than returning
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False.
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"""
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__slots__ = ('name', 'type_var', 'impl_type', 'type_checker')
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def __new__(cls, *args, **kwds):
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"""Constructor.
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This only exists to give a better error message in case
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someone tries to subclass a type alias (not a good idea).
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"""
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if (len(args) == 3 and
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isinstance(args[0], str) and
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isinstance(args[1], tuple)):
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# Close enough.
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raise TypeError("A type alias cannot be subclassed")
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return object.__new__(cls)
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def __init__(self, name, type_var, impl_type, type_checker):
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"""Initializer.
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Args:
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name: The name, e.g. 'Pattern'.
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type_var: The type parameter, e.g. AnyStr, or the
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specific type, e.g. str.
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impl_type: The implementation type.
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type_checker: Function that takes an impl_type instance.
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and returns a value that should be a type_var instance.
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"""
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assert isinstance(name, str), repr(name)
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assert isinstance(type_var, type), repr(type_var)
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assert isinstance(impl_type, type), repr(impl_type)
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assert not isinstance(impl_type, TypingMeta), repr(impl_type)
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self.name = name
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self.type_var = type_var
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self.impl_type = impl_type
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self.type_checker = type_checker
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def __repr__(self):
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return "%s[%s]" % (self.name, _type_repr(self.type_var))
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def __getitem__(self, parameter):
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assert isinstance(parameter, type), repr(parameter)
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if not isinstance(self.type_var, TypeVar):
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raise TypeError("%s cannot be further parameterized." % self)
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if self.type_var.__constraints__:
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if not issubclass(parameter, Union[self.type_var.__constraints__]):
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raise TypeError("%s is not a valid substitution for %s." %
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(parameter, self.type_var))
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return self.__class__(self.name, parameter,
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self.impl_type, self.type_checker)
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def __instancecheck__(self, obj):
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raise TypeError("Type aliases cannot be used with isinstance().")
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def __subclasscheck__(self, cls):
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if cls is Any:
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return True
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if isinstance(cls, _TypeAlias):
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# Covariance. For now, we compare by name.
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return (cls.name == self.name and
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issubclass(cls.type_var, self.type_var))
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else:
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# Note that this is too lenient, because the
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# implementation type doesn't carry information about
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# whether it is about bytes or str (for example).
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return issubclass(cls, self.impl_type)
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def _has_type_var(t):
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return t is not None and isinstance(t, TypingMeta) and t._has_type_var()
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def _eval_type(t, globalns, localns):
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if isinstance(t, TypingMeta):
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return t._eval_type(globalns, localns)
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else:
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return t
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def _type_check(arg, msg):
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"""Check that the argument is a type, and return it.
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As a special case, accept None and return type(None) instead.
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Also, _TypeAlias instances (e.g. Match, Pattern) are acceptable.
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The msg argument is a human-readable error message, e.g.
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"Union[arg, ...]: arg should be a type."
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We append the repr() of the actual value (truncated to 100 chars).
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"""
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if arg is None:
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return type(None)
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if isinstance(arg, str):
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arg = _ForwardRef(arg)
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if not isinstance(arg, (type, _TypeAlias)):
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raise TypeError(msg + " Got %.100r." % (arg,))
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return arg
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def _type_repr(obj):
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"""Return the repr() of an object, special-casing types.
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If obj is a type, we return a shorter version than the default
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type.__repr__, based on the module and qualified name, which is
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typically enough to uniquely identify a type. For everything
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else, we fall back on repr(obj).
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"""
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if isinstance(obj, type) and not isinstance(obj, TypingMeta):
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if obj.__module__ == 'builtins':
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return _qualname(obj)
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else:
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return '%s.%s' % (obj.__module__, _qualname(obj))
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else:
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return repr(obj)
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class AnyMeta(TypingMeta):
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"""Metaclass for Any."""
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def __new__(cls, name, bases, namespace, _root=False):
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self = super().__new__(cls, name, bases, namespace, _root=_root)
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return self
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def __instancecheck__(self, obj):
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raise TypeError("Any cannot be used with isinstance().")
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def __subclasscheck__(self, cls):
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if not isinstance(cls, type):
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return super().__subclasscheck__(cls) # To TypeError.
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return True
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class Any(Final, metaclass=AnyMeta, _root=True):
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"""Special type indicating an unconstrained type.
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- Any object is an instance of Any.
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- Any class is a subclass of Any.
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- As a special case, Any and object are subclasses of each other.
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"""
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__slots__ = ()
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class TypeVar(TypingMeta, metaclass=TypingMeta, _root=True):
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"""Type variable.
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Usage::
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T = TypeVar('T') # Can be anything
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A = TypeVar('A', str, bytes) # Must be str or bytes
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Type variables exist primarily for the benefit of static type
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checkers. They serve as the parameters for generic types as well
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as for generic function definitions. See class Generic for more
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information on generic types. Generic functions work as follows:
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def repeat(x: T, n: int) -> Sequence[T]:
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'''Return a list containing n references to x.'''
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return [x]*n
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def longest(x: A, y: A) -> A:
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'''Return the longest of two strings.'''
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return x if len(x) >= len(y) else y
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The latter example's signature is essentially the overloading
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of (str, str) -> str and (bytes, bytes) -> bytes. Also note
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that if the arguments are instances of some subclass of str,
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the return type is still plain str.
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At runtime, isinstance(x, T) will raise TypeError. However,
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issubclass(C, T) is true for any class C, and issubclass(str, A)
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and issubclass(bytes, A) are true, and issubclass(int, A) is
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false.
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Type variables may be marked covariant or contravariant by passing
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covariant=True or contravariant=True. See PEP 484 for more
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details. By default type variables are invariant.
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Type variables can be introspected. e.g.:
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T.__name__ == 'T'
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T.__constraints__ == ()
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T.__covariant__ == False
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T.__contravariant__ = False
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A.__constraints__ == (str, bytes)
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"""
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def __new__(cls, name, *constraints, bound=None,
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covariant=False, contravariant=False):
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self = super().__new__(cls, name, (Final,), {}, _root=True)
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if covariant and contravariant:
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raise ValueError("Bivariant type variables are not supported.")
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self.__covariant__ = bool(covariant)
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self.__contravariant__ = bool(contravariant)
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if constraints and bound is not None:
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raise TypeError("Constraints cannot be combined with bound=...")
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if constraints and len(constraints) == 1:
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raise TypeError("A single constraint is not allowed")
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msg = "TypeVar(name, constraint, ...): constraints must be types."
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self.__constraints__ = tuple(_type_check(t, msg) for t in constraints)
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if bound:
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self.__bound__ = _type_check(bound, "Bound must be a type.")
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else:
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self.__bound__ = None
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return self
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|
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def _has_type_var(self):
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return True
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|
|
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def __repr__(self):
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if self.__covariant__:
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prefix = '+'
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elif self.__contravariant__:
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prefix = '-'
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else:
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prefix = '~'
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return prefix + self.__name__
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|
|
|
def __instancecheck__(self, instance):
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raise TypeError("Type variables cannot be used with isinstance().")
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|
|
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def __subclasscheck__(self, cls):
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# TODO: Make this raise TypeError too?
|
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if cls is self:
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return True
|
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if cls is Any:
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return True
|
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if self.__bound__ is not None:
|
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return issubclass(cls, self.__bound__)
|
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if self.__constraints__:
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return any(issubclass(cls, c) for c in self.__constraints__)
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return True
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|
|
|
|
|
# Some unconstrained type variables. These are used by the container types.
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T = TypeVar('T') # Any type.
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KT = TypeVar('KT') # Key type.
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VT = TypeVar('VT') # Value type.
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T_co = TypeVar('T_co', covariant=True) # Any type covariant containers.
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V_co = TypeVar('V_co', covariant=True) # Any type covariant containers.
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VT_co = TypeVar('VT_co', covariant=True) # Value type covariant containers.
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T_contra = TypeVar('T_contra', contravariant=True) # Ditto contravariant.
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|
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# A useful type variable with constraints. This represents string types.
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# TODO: What about bytearray, memoryview?
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AnyStr = TypeVar('AnyStr', bytes, str)
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|
|
|
|
|
class UnionMeta(TypingMeta):
|
|
"""Metaclass for Union."""
|
|
|
|
def __new__(cls, name, bases, namespace, parameters=None, _root=False):
|
|
if parameters is None:
|
|
return super().__new__(cls, name, bases, namespace, _root=_root)
|
|
if not isinstance(parameters, tuple):
|
|
raise TypeError("Expected parameters=<tuple>")
|
|
# Flatten out Union[Union[...], ...] and type-check non-Union args.
|
|
params = []
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msg = "Union[arg, ...]: each arg must be a type."
|
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for p in parameters:
|
|
if isinstance(p, UnionMeta):
|
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params.extend(p.__union_params__)
|
|
else:
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params.append(_type_check(p, msg))
|
|
# 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:
|
|
new_params.append(t)
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all_params.remove(t)
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|
params = new_params
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|
assert not all_params, all_params
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|
# Weed out subclasses.
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|
# E.g. Union[int, Employee, Manager] == Union[int, Employee].
|
|
# If Any or object is present it will be the sole survivor.
|
|
# If both Any and object are present, Any wins.
|
|
# Never discard type variables, except against Any.
|
|
# (In particular, Union[str, AnyStr] != AnyStr.)
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|
all_params = set(params)
|
|
for t1 in params:
|
|
if t1 is Any:
|
|
return Any
|
|
if isinstance(t1, TypeVar):
|
|
continue
|
|
if any(issubclass(t1, t2)
|
|
for t2 in all_params - {t1} if not isinstance(t2, TypeVar)):
|
|
all_params.remove(t1)
|
|
# It's not a union if there's only one type left.
|
|
if len(all_params) == 1:
|
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return all_params.pop()
|
|
# Create a new class with these params.
|
|
self = super().__new__(cls, name, bases, {}, _root=True)
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|
self.__union_params__ = tuple(t for t in params if t in all_params)
|
|
self.__union_set_params__ = frozenset(self.__union_params__)
|
|
return self
|
|
|
|
def _eval_type(self, globalns, localns):
|
|
p = tuple(_eval_type(t, globalns, localns)
|
|
for t in self.__union_params__)
|
|
if p == self.__union_params__:
|
|
return self
|
|
else:
|
|
return self.__class__(self.__name__, self.__bases__, {},
|
|
p, _root=True)
|
|
|
|
def _has_type_var(self):
|
|
if self.__union_params__:
|
|
for t in self.__union_params__:
|
|
if _has_type_var(t):
|
|
return True
|
|
return False
|
|
|
|
def __repr__(self):
|
|
r = super().__repr__()
|
|
if self.__union_params__:
|
|
r += '[%s]' % (', '.join(_type_repr(t)
|
|
for t in self.__union_params__))
|
|
return r
|
|
|
|
def __getitem__(self, parameters):
|
|
if self.__union_params__ is not None:
|
|
raise TypeError(
|
|
"Cannot subscript an existing Union. Use Union[u, t] instead.")
|
|
if parameters == ():
|
|
raise TypeError("Cannot take a Union of no types.")
|
|
if not isinstance(parameters, tuple):
|
|
parameters = (parameters,)
|
|
return self.__class__(self.__name__, self.__bases__,
|
|
dict(self.__dict__), parameters, _root=True)
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, UnionMeta):
|
|
return NotImplemented
|
|
return self.__union_set_params__ == other.__union_set_params__
|
|
|
|
def __hash__(self):
|
|
return hash(self.__union_set_params__)
|
|
|
|
def __instancecheck__(self, obj):
|
|
raise TypeError("Unions cannot be used with isinstance().")
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if cls is Any:
|
|
return True
|
|
if self.__union_params__ is None:
|
|
return isinstance(cls, UnionMeta)
|
|
elif isinstance(cls, UnionMeta):
|
|
if cls.__union_params__ is None:
|
|
return False
|
|
return all(issubclass(c, self) for c in (cls.__union_params__))
|
|
elif isinstance(cls, TypeVar):
|
|
if cls in self.__union_params__:
|
|
return True
|
|
if cls.__constraints__:
|
|
return issubclass(Union[cls.__constraints__], self)
|
|
return False
|
|
else:
|
|
return any(issubclass(cls, t) for t in self.__union_params__)
|
|
|
|
|
|
class Union(Final, metaclass=UnionMeta, _root=True):
|
|
"""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
|
|
type(None).
|
|
|
|
- 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]
|
|
|
|
- When two arguments have a subclass relationship, the least
|
|
derived argument is kept, e.g.::
|
|
|
|
class Employee: pass
|
|
class Manager(Employee): pass
|
|
Union[int, Employee, Manager] == Union[int, Employee]
|
|
Union[Manager, int, Employee] == Union[int, Employee]
|
|
Union[Employee, Manager] == Employee
|
|
|
|
- Corollary: if Any is present it is the sole survivor, e.g.::
|
|
|
|
Union[int, Any] == Any
|
|
|
|
- Similar for object::
|
|
|
|
Union[int, object] == object
|
|
|
|
- To cut a tie: Union[object, Any] == Union[Any, object] == Any.
|
|
|
|
- You cannot subclass or instantiate a union.
|
|
|
|
- You cannot write Union[X][Y] (what would it mean?).
|
|
|
|
- You can use Optional[X] as a shorthand for Union[X, None].
|
|
"""
|
|
|
|
# Unsubscripted Union type has params set to None.
|
|
__union_params__ = None
|
|
__union_set_params__ = None
|
|
|
|
|
|
class OptionalMeta(TypingMeta):
|
|
"""Metaclass for Optional."""
|
|
|
|
def __new__(cls, name, bases, namespace, _root=False):
|
|
return super().__new__(cls, name, bases, namespace, _root=_root)
|
|
|
|
def __getitem__(self, arg):
|
|
arg = _type_check(arg, "Optional[t] requires a single type.")
|
|
return Union[arg, type(None)]
|
|
|
|
|
|
class Optional(Final, metaclass=OptionalMeta, _root=True):
|
|
"""Optional type.
|
|
|
|
Optional[X] is equivalent to Union[X, type(None)].
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
|
|
class TupleMeta(TypingMeta):
|
|
"""Metaclass for Tuple."""
|
|
|
|
def __new__(cls, name, bases, namespace, parameters=None,
|
|
use_ellipsis=False, _root=False):
|
|
self = super().__new__(cls, name, bases, namespace, _root=_root)
|
|
self.__tuple_params__ = parameters
|
|
self.__tuple_use_ellipsis__ = use_ellipsis
|
|
return self
|
|
|
|
def _has_type_var(self):
|
|
if self.__tuple_params__:
|
|
for t in self.__tuple_params__:
|
|
if _has_type_var(t):
|
|
return True
|
|
return False
|
|
|
|
def _eval_type(self, globalns, localns):
|
|
tp = self.__tuple_params__
|
|
if tp is None:
|
|
return self
|
|
p = tuple(_eval_type(t, globalns, localns) for t in tp)
|
|
if p == self.__tuple_params__:
|
|
return self
|
|
else:
|
|
return self.__class__(self.__name__, self.__bases__, {},
|
|
p, _root=True)
|
|
|
|
def __repr__(self):
|
|
r = super().__repr__()
|
|
if self.__tuple_params__ is not None:
|
|
params = [_type_repr(p) for p in self.__tuple_params__]
|
|
if self.__tuple_use_ellipsis__:
|
|
params.append('...')
|
|
r += '[%s]' % (
|
|
', '.join(params))
|
|
return r
|
|
|
|
def __getitem__(self, parameters):
|
|
if self.__tuple_params__ is not None:
|
|
raise TypeError("Cannot re-parameterize %r" % (self,))
|
|
if not isinstance(parameters, tuple):
|
|
parameters = (parameters,)
|
|
if len(parameters) == 2 and parameters[1] == Ellipsis:
|
|
parameters = parameters[:1]
|
|
use_ellipsis = True
|
|
msg = "Tuple[t, ...]: t must be a type."
|
|
else:
|
|
use_ellipsis = False
|
|
msg = "Tuple[t0, t1, ...]: each t must be a type."
|
|
parameters = tuple(_type_check(p, msg) for p in parameters)
|
|
return self.__class__(self.__name__, self.__bases__,
|
|
dict(self.__dict__), parameters,
|
|
use_ellipsis=use_ellipsis, _root=True)
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, TupleMeta):
|
|
return NotImplemented
|
|
return self.__tuple_params__ == other.__tuple_params__
|
|
|
|
def __hash__(self):
|
|
return hash(self.__tuple_params__)
|
|
|
|
def __instancecheck__(self, obj):
|
|
raise TypeError("Tuples cannot be used with isinstance().")
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if cls is Any:
|
|
return True
|
|
if not isinstance(cls, type):
|
|
return super().__subclasscheck__(cls) # To TypeError.
|
|
if issubclass(cls, tuple):
|
|
return True # Special case.
|
|
if not isinstance(cls, TupleMeta):
|
|
return super().__subclasscheck__(cls) # False.
|
|
if self.__tuple_params__ is None:
|
|
return True
|
|
if cls.__tuple_params__ is None:
|
|
return False # ???
|
|
if cls.__tuple_use_ellipsis__ != self.__tuple_use_ellipsis__:
|
|
return False
|
|
# Covariance.
|
|
return (len(self.__tuple_params__) == len(cls.__tuple_params__) and
|
|
all(issubclass(x, p)
|
|
for x, p in zip(cls.__tuple_params__,
|
|
self.__tuple_params__)))
|
|
|
|
|
|
class Tuple(Final, metaclass=TupleMeta, _root=True):
|
|
"""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 Sequence[T].
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
|
|
class CallableMeta(TypingMeta):
|
|
"""Metaclass for Callable."""
|
|
|
|
def __new__(cls, name, bases, namespace, _root=False,
|
|
args=None, result=None):
|
|
if args is None and result is None:
|
|
pass # Must be 'class Callable'.
|
|
else:
|
|
if args is not Ellipsis:
|
|
if not isinstance(args, list):
|
|
raise TypeError("Callable[args, result]: "
|
|
"args must be a list."
|
|
" Got %.100r." % (args,))
|
|
msg = "Callable[[arg, ...], result]: each arg must be a type."
|
|
args = tuple(_type_check(arg, msg) for arg in args)
|
|
msg = "Callable[args, result]: result must be a type."
|
|
result = _type_check(result, msg)
|
|
self = super().__new__(cls, name, bases, namespace, _root=_root)
|
|
self.__args__ = args
|
|
self.__result__ = result
|
|
return self
|
|
|
|
def _has_type_var(self):
|
|
if self.__args__:
|
|
for t in self.__args__:
|
|
if _has_type_var(t):
|
|
return True
|
|
return _has_type_var(self.__result__)
|
|
|
|
def _eval_type(self, globalns, localns):
|
|
if self.__args__ is None and self.__result__ is None:
|
|
return self
|
|
if self.__args__ is Ellipsis:
|
|
args = self.__args__
|
|
else:
|
|
args = [_eval_type(t, globalns, localns) for t in self.__args__]
|
|
result = _eval_type(self.__result__, globalns, localns)
|
|
if args == self.__args__ and result == self.__result__:
|
|
return self
|
|
else:
|
|
return self.__class__(self.__name__, self.__bases__, {},
|
|
args=args, result=result, _root=True)
|
|
|
|
def __repr__(self):
|
|
r = super().__repr__()
|
|
if self.__args__ is not None or self.__result__ is not None:
|
|
if self.__args__ is Ellipsis:
|
|
args_r = '...'
|
|
else:
|
|
args_r = '[%s]' % ', '.join(_type_repr(t)
|
|
for t in self.__args__)
|
|
r += '[%s, %s]' % (args_r, _type_repr(self.__result__))
|
|
return r
|
|
|
|
def __getitem__(self, parameters):
|
|
if self.__args__ is not None or self.__result__ is not None:
|
|
raise TypeError("This Callable type is already parameterized.")
|
|
if not isinstance(parameters, tuple) or len(parameters) != 2:
|
|
raise TypeError(
|
|
"Callable must be used as Callable[[arg, ...], result].")
|
|
args, result = parameters
|
|
return self.__class__(self.__name__, self.__bases__,
|
|
dict(self.__dict__), _root=True,
|
|
args=args, result=result)
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, CallableMeta):
|
|
return NotImplemented
|
|
return (self.__args__ == other.__args__ and
|
|
self.__result__ == other.__result__)
|
|
|
|
def __hash__(self):
|
|
return hash(self.__args__) ^ hash(self.__result__)
|
|
|
|
def __instancecheck__(self, obj):
|
|
# For unparametrized Callable we allow this, because
|
|
# typing.Callable should be equivalent to
|
|
# collections.abc.Callable.
|
|
if self.__args__ is None and self.__result__ is None:
|
|
return isinstance(obj, collections_abc.Callable)
|
|
else:
|
|
raise TypeError("Callable[] cannot be used with isinstance().")
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if cls is Any:
|
|
return True
|
|
if not isinstance(cls, CallableMeta):
|
|
return super().__subclasscheck__(cls)
|
|
if self.__args__ is None and self.__result__ is None:
|
|
return True
|
|
# We're not doing covariance or contravariance -- this is *invariance*.
|
|
return self == cls
|
|
|
|
|
|
class Callable(Final, metaclass=CallableMeta, _root=True):
|
|
"""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; 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.
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
|
|
def _gorg(a):
|
|
"""Return the farthest origin of a generic class."""
|
|
assert isinstance(a, GenericMeta)
|
|
while a.__origin__ is not None:
|
|
a = a.__origin__
|
|
return a
|
|
|
|
|
|
def _geqv(a, b):
|
|
"""Return whether two generic classes are equivalent.
|
|
|
|
The intention is to consider generic class X and any of its
|
|
parameterized forms (X[T], X[int], etc.) as equivalent.
|
|
|
|
However, X is not equivalent to a subclass of X.
|
|
|
|
The relation is reflexive, symmetric and transitive.
|
|
"""
|
|
assert isinstance(a, GenericMeta) and isinstance(b, GenericMeta)
|
|
# Reduce each to its origin.
|
|
return _gorg(a) is _gorg(b)
|
|
|
|
|
|
class GenericMeta(TypingMeta, abc.ABCMeta):
|
|
"""Metaclass for generic types."""
|
|
|
|
# TODO: Constrain more how Generic is used; only a few
|
|
# standard patterns should be allowed.
|
|
|
|
# TODO: Use a more precise rule than matching __name__ to decide
|
|
# whether two classes are the same. Also, save the formal
|
|
# parameters. (These things are related! A solution lies in
|
|
# using origin.)
|
|
|
|
__extra__ = None
|
|
|
|
def __new__(cls, name, bases, namespace,
|
|
parameters=None, origin=None, extra=None):
|
|
if parameters is None:
|
|
# Extract parameters from direct base classes. Only
|
|
# direct bases are considered and only those that are
|
|
# themselves generic, and parameterized with type
|
|
# variables. Don't use bases like Any, Union, Tuple,
|
|
# Callable or type variables.
|
|
params = None
|
|
for base in bases:
|
|
if isinstance(base, TypingMeta):
|
|
if not isinstance(base, GenericMeta):
|
|
raise TypeError(
|
|
"You cannot inherit from magic class %s" %
|
|
repr(base))
|
|
if base.__parameters__ is None:
|
|
continue # The base is unparameterized.
|
|
for bp in base.__parameters__:
|
|
if _has_type_var(bp) and not isinstance(bp, TypeVar):
|
|
raise TypeError(
|
|
"Cannot inherit from a generic class "
|
|
"parameterized with "
|
|
"non-type-variable %s" % bp)
|
|
if params is None:
|
|
params = []
|
|
if bp not in params:
|
|
params.append(bp)
|
|
if params is not None:
|
|
parameters = tuple(params)
|
|
self = super().__new__(cls, name, bases, namespace, _root=True)
|
|
self.__parameters__ = parameters
|
|
if extra is not None:
|
|
self.__extra__ = extra
|
|
# Else __extra__ is inherited, eventually from the
|
|
# (meta-)class default above.
|
|
self.__origin__ = origin
|
|
return self
|
|
|
|
def _has_type_var(self):
|
|
if self.__parameters__:
|
|
for t in self.__parameters__:
|
|
if _has_type_var(t):
|
|
return True
|
|
return False
|
|
|
|
def __repr__(self):
|
|
r = super().__repr__()
|
|
if self.__parameters__ is not None:
|
|
r += '[%s]' % (
|
|
', '.join(_type_repr(p) for p in self.__parameters__))
|
|
return r
|
|
|
|
def __eq__(self, other):
|
|
if not isinstance(other, GenericMeta):
|
|
return NotImplemented
|
|
return (_geqv(self, other) and
|
|
self.__parameters__ == other.__parameters__)
|
|
|
|
def __hash__(self):
|
|
return hash((self.__name__, self.__parameters__))
|
|
|
|
def __getitem__(self, params):
|
|
if not isinstance(params, tuple):
|
|
params = (params,)
|
|
if not params:
|
|
raise TypeError("Cannot have empty parameter list")
|
|
msg = "Parameters to generic types must be types."
|
|
params = tuple(_type_check(p, msg) for p in params)
|
|
if self.__parameters__ is None:
|
|
for p in params:
|
|
if not isinstance(p, TypeVar):
|
|
raise TypeError("Initial parameters must be "
|
|
"type variables; got %s" % p)
|
|
if len(set(params)) != len(params):
|
|
raise TypeError("All type variables in Generic[...] must be distinct.")
|
|
else:
|
|
if len(params) != len(self.__parameters__):
|
|
raise TypeError("Cannot change parameter count from %d to %d" %
|
|
(len(self.__parameters__), len(params)))
|
|
for new, old in zip(params, self.__parameters__):
|
|
if isinstance(old, TypeVar):
|
|
if not old.__constraints__:
|
|
# Substituting for an unconstrained TypeVar is OK.
|
|
continue
|
|
if issubclass(new, Union[old.__constraints__]):
|
|
# Specializing a constrained type variable is OK.
|
|
continue
|
|
if not issubclass(new, old):
|
|
raise TypeError(
|
|
"Cannot substitute %s for %s in %s" %
|
|
(_type_repr(new), _type_repr(old), self))
|
|
|
|
return self.__class__(self.__name__, self.__bases__,
|
|
dict(self.__dict__),
|
|
parameters=params,
|
|
origin=self,
|
|
extra=self.__extra__)
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if cls is Any:
|
|
return True
|
|
if isinstance(cls, GenericMeta):
|
|
# For a class C(Generic[T]) where T is co-variant,
|
|
# C[X] is a subclass of C[Y] iff X is a subclass of Y.
|
|
origin = self.__origin__
|
|
if origin is not None and origin is cls.__origin__:
|
|
assert len(self.__parameters__) == len(origin.__parameters__)
|
|
assert len(cls.__parameters__) == len(origin.__parameters__)
|
|
for p_self, p_cls, p_origin in zip(self.__parameters__,
|
|
cls.__parameters__,
|
|
origin.__parameters__):
|
|
if isinstance(p_origin, TypeVar):
|
|
if p_origin.__covariant__:
|
|
# Covariant -- p_cls must be a subclass of p_self.
|
|
if not issubclass(p_cls, p_self):
|
|
break
|
|
elif p_origin.__contravariant__:
|
|
# Contravariant. I think it's the opposite. :-)
|
|
if not issubclass(p_self, p_cls):
|
|
break
|
|
else:
|
|
# Invariant -- p_cls and p_self must equal.
|
|
if p_self != p_cls:
|
|
break
|
|
else:
|
|
# If the origin's parameter is not a typevar,
|
|
# insist on invariance.
|
|
if p_self != p_cls:
|
|
break
|
|
else:
|
|
return True
|
|
# If we break out of the loop, the superclass gets a chance.
|
|
if super().__subclasscheck__(cls):
|
|
return True
|
|
if self.__extra__ is None or isinstance(cls, GenericMeta):
|
|
return False
|
|
return issubclass(cls, self.__extra__)
|
|
|
|
|
|
class Generic(metaclass=GenericMeta):
|
|
"""Abstract base class for generic types.
|
|
|
|
A generic type is typically declared by inheriting from an
|
|
instantiation of this class 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, key: KT, default: VT) -> VT:
|
|
try:
|
|
return mapping[key]
|
|
except KeyError:
|
|
return default
|
|
|
|
For clarity the type variables may be redefined, e.g.::
|
|
|
|
X = TypeVar('X')
|
|
Y = TypeVar('Y')
|
|
def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
|
|
# Same body as above.
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
next_in_mro = object
|
|
# Look for the last occurrence of Generic or Generic[...].
|
|
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.__new__(_gorg(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__
|
|
pos_count = code.co_argcount
|
|
kw_count = code.co_kwonlyargcount
|
|
arg_names = code.co_varnames
|
|
kwarg_names = arg_names[pos_count:pos_count + kw_count]
|
|
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
|
|
|
|
|
|
def get_type_hints(obj, globalns=None, localns=None):
|
|
"""Return type hints for a function or method 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.
|
|
|
|
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, and these are also used as the locals. If the
|
|
object does not appear to have globals, an exception is raised.
|
|
|
|
- If one dict argument is passed, it is used for both globals and
|
|
locals.
|
|
|
|
- If two dict arguments are passed, they specify globals and
|
|
locals, respectively.
|
|
"""
|
|
if getattr(obj, '__no_type_check__', None):
|
|
return {}
|
|
if globalns is None:
|
|
globalns = getattr(obj, '__globals__', {})
|
|
if localns is None:
|
|
localns = globalns
|
|
elif localns is None:
|
|
localns = globalns
|
|
defaults = _get_defaults(obj)
|
|
hints = dict(obj.__annotations__)
|
|
for name, value in hints.items():
|
|
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
|
|
|
|
|
|
# TODO: Also support this as a class decorator.
|
|
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 defined in that class (but not
|
|
to methods defined in its superclasses or subclasses).
|
|
|
|
This mutates the function(s) in place.
|
|
"""
|
|
if isinstance(arg, type):
|
|
for obj in arg.__dict__.values():
|
|
if isinstance(obj, types.FunctionType):
|
|
obj.__no_type_check__ = True
|
|
else:
|
|
arg.__no_type_check__ = True
|
|
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.
|
|
"""
|
|
|
|
@functools.wraps(decorator)
|
|
def wrapped_decorator(*args, **kwds):
|
|
func = decorator(*args, **kwds)
|
|
func = no_type_check(func)
|
|
return func
|
|
|
|
return wrapped_decorator
|
|
|
|
|
|
def overload(func):
|
|
raise RuntimeError("Overloading is only supported in library stubs")
|
|
|
|
|
|
class _ProtocolMeta(GenericMeta):
|
|
"""Internal metaclass for _Protocol.
|
|
|
|
This exists so _Protocol classes can be generic without deriving
|
|
from Generic.
|
|
"""
|
|
|
|
def __instancecheck__(self, obj):
|
|
raise TypeError("Protocols cannot be used with isinstance().")
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if not self._is_protocol:
|
|
# No structural checks since this isn't a protocol.
|
|
return NotImplemented
|
|
|
|
if self is _Protocol:
|
|
# Every class is a subclass of the empty protocol.
|
|
return True
|
|
|
|
# Find all attributes defined in the protocol.
|
|
attrs = self._get_protocol_attrs()
|
|
|
|
for attr in attrs:
|
|
if not any(attr in d.__dict__ for d in cls.__mro__):
|
|
return False
|
|
return True
|
|
|
|
def _get_protocol_attrs(self):
|
|
# Get all Protocol base classes.
|
|
protocol_bases = []
|
|
for c in self.__mro__:
|
|
if getattr(c, '_is_protocol', False) and c.__name__ != '_Protocol':
|
|
protocol_bases.append(c)
|
|
|
|
# Get attributes included in protocol.
|
|
attrs = set()
|
|
for base in protocol_bases:
|
|
for attr in base.__dict__.keys():
|
|
# Include attributes not defined in any non-protocol bases.
|
|
for c in self.__mro__:
|
|
if (c is not base and attr in c.__dict__ and
|
|
not getattr(c, '_is_protocol', False)):
|
|
break
|
|
else:
|
|
if (not attr.startswith('_abc_') and
|
|
attr != '__abstractmethods__' and
|
|
attr != '_is_protocol' and
|
|
attr != '__dict__' and
|
|
attr != '__slots__' and
|
|
attr != '_get_protocol_attrs' and
|
|
attr != '__parameters__' and
|
|
attr != '__origin__' and
|
|
attr != '__module__'):
|
|
attrs.add(attr)
|
|
|
|
return attrs
|
|
|
|
|
|
class _Protocol(metaclass=_ProtocolMeta):
|
|
"""Internal base class for protocol classes.
|
|
|
|
This implements a simple-minded structural isinstance check
|
|
(similar but more general than the one-offs in collections.abc
|
|
such as Hashable).
|
|
"""
|
|
|
|
__slots__ = ()
|
|
|
|
_is_protocol = True
|
|
|
|
|
|
# Various ABCs mimicking those in collections.abc.
|
|
# A few are simply re-exported for completeness.
|
|
|
|
Hashable = collections_abc.Hashable # Not generic.
|
|
|
|
|
|
class Iterable(Generic[T_co], extra=collections_abc.Iterable):
|
|
__slots__ = ()
|
|
|
|
|
|
class Iterator(Iterable[T_co], extra=collections_abc.Iterator):
|
|
__slots__ = ()
|
|
|
|
|
|
class SupportsInt(_Protocol):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __int__(self) -> int:
|
|
pass
|
|
|
|
|
|
class SupportsFloat(_Protocol):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __float__(self) -> float:
|
|
pass
|
|
|
|
|
|
class SupportsComplex(_Protocol):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __complex__(self) -> complex:
|
|
pass
|
|
|
|
|
|
class SupportsBytes(_Protocol):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __bytes__(self) -> bytes:
|
|
pass
|
|
|
|
|
|
class SupportsAbs(_Protocol[T_co]):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __abs__(self) -> T_co:
|
|
pass
|
|
|
|
|
|
class SupportsRound(_Protocol[T_co]):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __round__(self, ndigits: int = 0) -> T_co:
|
|
pass
|
|
|
|
|
|
class Reversible(_Protocol[T_co]):
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def __reversed__(self) -> 'Iterator[T_co]':
|
|
pass
|
|
|
|
|
|
Sized = collections_abc.Sized # Not generic.
|
|
|
|
|
|
class Container(Generic[T_co], extra=collections_abc.Container):
|
|
__slots__ = ()
|
|
|
|
|
|
# Callable was defined earlier.
|
|
|
|
|
|
class AbstractSet(Sized, Iterable[T_co], Container[T_co],
|
|
extra=collections_abc.Set):
|
|
pass
|
|
|
|
|
|
class MutableSet(AbstractSet[T], extra=collections_abc.MutableSet):
|
|
pass
|
|
|
|
|
|
# NOTE: Only the value type is covariant.
|
|
class Mapping(Sized, Iterable[KT], Container[KT], Generic[VT_co],
|
|
extra=collections_abc.Mapping):
|
|
pass
|
|
|
|
|
|
class MutableMapping(Mapping[KT, VT], extra=collections_abc.MutableMapping):
|
|
pass
|
|
|
|
|
|
class Sequence(Sized, Iterable[T_co], Container[T_co],
|
|
extra=collections_abc.Sequence):
|
|
pass
|
|
|
|
|
|
class MutableSequence(Sequence[T], extra=collections_abc.MutableSequence):
|
|
pass
|
|
|
|
|
|
class ByteString(Sequence[int], extra=collections_abc.ByteString):
|
|
pass
|
|
|
|
|
|
ByteString.register(type(memoryview(b'')))
|
|
|
|
|
|
class List(list, MutableSequence[T]):
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
if _geqv(cls, List):
|
|
raise TypeError("Type List cannot be instantiated; "
|
|
"use list() instead")
|
|
return list.__new__(cls, *args, **kwds)
|
|
|
|
|
|
class Set(set, MutableSet[T]):
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
if _geqv(cls, Set):
|
|
raise TypeError("Type Set cannot be instantiated; "
|
|
"use set() instead")
|
|
return set.__new__(cls, *args, **kwds)
|
|
|
|
|
|
class _FrozenSetMeta(GenericMeta):
|
|
"""This metaclass ensures set is not a subclass of FrozenSet.
|
|
|
|
Without this metaclass, set would be considered a subclass of
|
|
FrozenSet, because FrozenSet.__extra__ is collections.abc.Set, and
|
|
set is a subclass of that.
|
|
"""
|
|
|
|
def __subclasscheck__(self, cls):
|
|
if issubclass(cls, Set):
|
|
return False
|
|
return super().__subclasscheck__(cls)
|
|
|
|
|
|
class FrozenSet(frozenset, AbstractSet[T_co], metaclass=_FrozenSetMeta):
|
|
__slots__ = ()
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
if _geqv(cls, FrozenSet):
|
|
raise TypeError("Type FrozenSet cannot be instantiated; "
|
|
"use frozenset() instead")
|
|
return frozenset.__new__(cls, *args, **kwds)
|
|
|
|
|
|
class MappingView(Sized, Iterable[T_co], extra=collections_abc.MappingView):
|
|
pass
|
|
|
|
|
|
class KeysView(MappingView[KT], AbstractSet[KT],
|
|
extra=collections_abc.KeysView):
|
|
pass
|
|
|
|
|
|
# TODO: Enable Set[Tuple[KT, VT_co]] instead of Generic[KT, VT_co].
|
|
class ItemsView(MappingView, Generic[KT, VT_co],
|
|
extra=collections_abc.ItemsView):
|
|
pass
|
|
|
|
|
|
class ValuesView(MappingView[VT_co], extra=collections_abc.ValuesView):
|
|
pass
|
|
|
|
|
|
class Dict(dict, MutableMapping[KT, VT]):
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
if _geqv(cls, Dict):
|
|
raise TypeError("Type Dict cannot be instantiated; "
|
|
"use dict() instead")
|
|
return dict.__new__(cls, *args, **kwds)
|
|
|
|
|
|
# Determine what base class to use for Generator.
|
|
if hasattr(collections_abc, 'Generator'):
|
|
# Sufficiently recent versions of 3.5 have a Generator ABC.
|
|
_G_base = collections_abc.Generator
|
|
else:
|
|
# Fall back on the exact type.
|
|
_G_base = types.GeneratorType
|
|
|
|
|
|
class Generator(Iterator[T_co], Generic[T_co, T_contra, V_co],
|
|
extra=_G_base):
|
|
__slots__ = ()
|
|
|
|
def __new__(cls, *args, **kwds):
|
|
if _geqv(cls, Generator):
|
|
raise TypeError("Type Generator cannot be instantiated; "
|
|
"create a subclass instead")
|
|
return super().__new__(cls, *args, **kwds)
|
|
|
|
|
|
def NamedTuple(typename, fields):
|
|
"""Typed version of namedtuple.
|
|
|
|
Usage::
|
|
|
|
Employee = typing.NamedTuple('Employee', [('name', str), 'id', int)])
|
|
|
|
This is equivalent to::
|
|
|
|
Employee = collections.namedtuple('Employee', ['name', 'id'])
|
|
|
|
The resulting class has one extra attribute: _field_types,
|
|
giving a dict mapping field names to types. (The field names
|
|
are in the _fields attribute, which is part of the namedtuple
|
|
API.)
|
|
"""
|
|
fields = [(n, t) for n, t in fields]
|
|
cls = collections.namedtuple(typename, [n for n, t in fields])
|
|
cls._field_types = dict(fields)
|
|
return cls
|
|
|
|
|
|
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__ = ()
|
|
|
|
@abstractproperty
|
|
def mode(self) -> str:
|
|
pass
|
|
|
|
@abstractproperty
|
|
def name(self) -> str:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def close(self) -> None:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def closed(self) -> bool:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def fileno(self) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def flush(self) -> None:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def isatty(self) -> bool:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def read(self, n: int = -1) -> AnyStr:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def readable(self) -> bool:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def readline(self, limit: int = -1) -> AnyStr:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def readlines(self, hint: int = -1) -> List[AnyStr]:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def seek(self, offset: int, whence: int = 0) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def seekable(self) -> bool:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def tell(self) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def truncate(self, size: int = None) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def writable(self) -> bool:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def write(self, s: AnyStr) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def writelines(self, lines: List[AnyStr]) -> None:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def __enter__(self) -> 'IO[AnyStr]':
|
|
pass
|
|
|
|
@abstractmethod
|
|
def __exit__(self, type, value, traceback) -> None:
|
|
pass
|
|
|
|
|
|
class BinaryIO(IO[bytes]):
|
|
"""Typed version of the return of open() in binary mode."""
|
|
|
|
__slots__ = ()
|
|
|
|
@abstractmethod
|
|
def write(self, s: Union[bytes, bytearray]) -> int:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def __enter__(self) -> 'BinaryIO':
|
|
pass
|
|
|
|
|
|
class TextIO(IO[str]):
|
|
"""Typed version of the return of open() in text mode."""
|
|
|
|
__slots__ = ()
|
|
|
|
@abstractproperty
|
|
def buffer(self) -> BinaryIO:
|
|
pass
|
|
|
|
@abstractproperty
|
|
def encoding(self) -> str:
|
|
pass
|
|
|
|
@abstractproperty
|
|
def errors(self) -> str:
|
|
pass
|
|
|
|
@abstractproperty
|
|
def line_buffering(self) -> bool:
|
|
pass
|
|
|
|
@abstractproperty
|
|
def newlines(self) -> Any:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def __enter__(self) -> 'TextIO':
|
|
pass
|
|
|
|
|
|
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 = _TypeAlias('Pattern', AnyStr, type(stdlib_re.compile('')),
|
|
lambda p: p.pattern)
|
|
Match = _TypeAlias('Match', AnyStr, type(stdlib_re.match('', '')),
|
|
lambda m: m.re.pattern)
|
|
|
|
|
|
class re:
|
|
"""Wrapper namespace for re type aliases."""
|
|
|
|
__all__ = ['Pattern', 'Match']
|
|
Pattern = Pattern
|
|
Match = Match
|
|
|
|
re.__name__ = __name__ + '.re'
|
|
sys.modules[re.__name__] = re
|